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Merge pull request #13146 from terfendail:bilateral_nan
This commit is contained in:
Alexander Alekhin
commit
605071e76f
@ -905,6 +905,11 @@ OPENCV_HAL_IMPL_AVX_CMP_OP_64BIT(v_int64x4)
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OPENCV_HAL_IMPL_AVX_CMP_OP_FLT(v_float32x8, ps)
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OPENCV_HAL_IMPL_AVX_CMP_OP_FLT(v_float64x4, pd)
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inline v_float32x8 v_not_nan(const v_float32x8& a)
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{ return v_float32x8(_mm256_cmp_ps(a.val, a.val, _CMP_ORD_Q)); }
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inline v_float64x4 v_not_nan(const v_float64x4& a)
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{ return v_float64x4(_mm256_cmp_pd(a.val, a.val, _CMP_ORD_Q)); }
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/** min/max **/
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OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_min, v_uint8x32, _mm256_min_epu8)
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OPENCV_HAL_IMPL_AVX_BIN_FUNC(v_max, v_uint8x32, _mm256_max_epu8)
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@ -683,6 +683,25 @@ OPENCV_HAL_IMPL_CMP_OP(==)
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For all types except 64-bit integer values. */
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OPENCV_HAL_IMPL_CMP_OP(!=)
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template<int n>
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inline v_reg<float, n> v_not_nan(const v_reg<float, n>& a)
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{
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typedef typename V_TypeTraits<float>::int_type itype;
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v_reg<float, n> c;
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for (int i = 0; i < n; i++)
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c.s[i] = V_TypeTraits<float>::reinterpret_from_int((itype)-(int)(a.s[i] == a.s[i]));
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return c;
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}
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template<int n>
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inline v_reg<double, n> v_not_nan(const v_reg<double, n>& a)
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{
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typedef typename V_TypeTraits<double>::int_type itype;
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v_reg<double, n> c;
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for (int i = 0; i < n; i++)
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c.s[i] = V_TypeTraits<double>::reinterpret_from_int((itype)-(int)(a.s[i] == a.s[i]));
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return c;
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}
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//! @brief Helper macro
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//! @ingroup core_hal_intrin_impl
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#define OPENCV_HAL_IMPL_ARITHM_OP(func, bin_op, cast_op, _Tp2) \
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@ -764,6 +764,13 @@ OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_int64x2, vreinterpretq_s64_u64, s64, u64)
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OPENCV_HAL_IMPL_NEON_INT_CMP_OP(v_float64x2, vreinterpretq_f64_u64, f64, u64)
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#endif
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inline v_float32x4 v_not_nan(const v_float32x4& a)
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{ return v_float32x4(vreinterpretq_f32_u32(vceqq_f32(a.val, a.val))); }
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#if CV_SIMD128_64F
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inline v_float64x2 v_not_nan(const v_float64x2& a)
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{ return v_float64x2(vreinterpretq_f64_u64(vceqq_f64(a.val, a.val))); }
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#endif
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OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint8x16, v_add_wrap, vaddq_u8)
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OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_int8x16, v_add_wrap, vaddq_s8)
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OPENCV_HAL_IMPL_NEON_BIN_FUNC(v_uint16x8, v_add_wrap, vaddq_u16)
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@ -1041,6 +1041,11 @@ inline _Tpvec operator != (const _Tpvec& a, const _Tpvec& b) \
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OPENCV_HAL_IMPL_SSE_64BIT_CMP_OP(v_uint64x2, v_reinterpret_as_u64)
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OPENCV_HAL_IMPL_SSE_64BIT_CMP_OP(v_int64x2, v_reinterpret_as_s64)
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inline v_float32x4 v_not_nan(const v_float32x4& a)
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{ return v_float32x4(_mm_cmpord_ps(a.val, a.val)); }
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inline v_float64x2 v_not_nan(const v_float64x2& a)
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{ return v_float64x2(_mm_cmpord_pd(a.val, a.val)); }
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OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_uint8x16, v_add_wrap, _mm_add_epi8)
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OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_int8x16, v_add_wrap, _mm_add_epi8)
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OPENCV_HAL_IMPL_SSE_BIN_FUNC(v_uint16x8, v_add_wrap, _mm_add_epi16)
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@ -607,6 +607,11 @@ OPENCV_HAL_IMPL_VSX_INT_CMP_OP(v_float64x2)
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OPENCV_HAL_IMPL_VSX_INT_CMP_OP(v_uint64x2)
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OPENCV_HAL_IMPL_VSX_INT_CMP_OP(v_int64x2)
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inline v_float32x4 v_not_nan(const v_float32x4& a)
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{ return v_float32x4(vec_cmpeq(a.val, a.val)); }
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inline v_float64x2 v_not_nan(const v_float64x2& a)
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{ return v_float64x2(vec_cmpeq(a.val, a.val)); }
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/** min/max **/
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OPENCV_HAL_IMPL_VSX_BIN_FUNC(v_min, vec_min)
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OPENCV_HAL_IMPL_VSX_BIN_FUNC(v_max, vec_max)
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@ -82,7 +82,84 @@ public:
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memset(buf.data(), 0, buf.size() * sizeof(float));
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float *sum = alignPtr(buf.data(), CV_SIMD_WIDTH);
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float *wsum = sum + alignSize(size.width, CV_SIMD_WIDTH);
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for( k = 0; k < maxk; k++ )
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k = 0;
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for(; k <= maxk-4; k+=4)
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{
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const uchar* ksptr0 = sptr + space_ofs[k];
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const uchar* ksptr1 = sptr + space_ofs[k+1];
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const uchar* ksptr2 = sptr + space_ofs[k+2];
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const uchar* ksptr3 = sptr + space_ofs[k+3];
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j = 0;
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#if CV_SIMD
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v_float32 kweight0 = vx_setall_f32(space_weight[k]);
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v_float32 kweight1 = vx_setall_f32(space_weight[k+1]);
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v_float32 kweight2 = vx_setall_f32(space_weight[k+2]);
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v_float32 kweight3 = vx_setall_f32(space_weight[k+3]);
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for (; j <= size.width - v_float32::nlanes; j += v_float32::nlanes)
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{
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v_uint32 rval = vx_load_expand_q(sptr + j);
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v_uint32 val = vx_load_expand_q(ksptr0 + j);
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v_float32 w = kweight0 * v_lut(color_weight, v_reinterpret_as_s32(v_absdiff(val, rval)));
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v_float32 v_wsum = vx_load_aligned(wsum + j) + w;
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v_float32 v_sum = v_muladd(v_cvt_f32(v_reinterpret_as_s32(val)), w, vx_load_aligned(sum + j));
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val = vx_load_expand_q(ksptr1 + j);
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w = kweight1 * v_lut(color_weight, v_reinterpret_as_s32(v_absdiff(val, rval)));
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v_wsum += w;
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v_sum = v_muladd(v_cvt_f32(v_reinterpret_as_s32(val)), w, v_sum);
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val = vx_load_expand_q(ksptr2 + j);
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w = kweight2 * v_lut(color_weight, v_reinterpret_as_s32(v_absdiff(val, rval)));
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v_wsum += w;
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v_sum = v_muladd(v_cvt_f32(v_reinterpret_as_s32(val)), w, v_sum);
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val = vx_load_expand_q(ksptr3 + j);
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w = kweight3 * v_lut(color_weight, v_reinterpret_as_s32(v_absdiff(val, rval)));
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v_wsum += w;
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v_sum = v_muladd(v_cvt_f32(v_reinterpret_as_s32(val)), w, v_sum);
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v_store_aligned(wsum + j, v_wsum);
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v_store_aligned(sum + j, v_sum);
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}
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#endif
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#if CV_SIMD128
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v_float32x4 kweight4 = v_load(space_weight + k);
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#endif
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for (; j < size.width; j++)
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{
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#if CV_SIMD128
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v_uint32x4 rval = v_setall_u32(sptr[j]);
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v_uint32x4 val(ksptr0[j], ksptr1[j], ksptr2[j], ksptr3[j]);
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v_float32x4 w = kweight4 * v_lut(color_weight, v_reinterpret_as_s32(v_absdiff(val, rval)));
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wsum[j] += v_reduce_sum(w);
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sum[j] += v_reduce_sum(v_cvt_f32(v_reinterpret_as_s32(val)) * w);
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#else
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int rval = sptr[j];
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int val = ksptr0[j];
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float w = space_weight[k] * color_weight[std::abs(val - rval)];
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wsum[j] += w;
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sum[j] += val * w;
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val = ksptr1[j];
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w = space_weight[k+1] * color_weight[std::abs(val - rval)];
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wsum[j] += w;
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sum[j] += val * w;
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val = ksptr2[j];
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w = space_weight[k+2] * color_weight[std::abs(val - rval)];
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wsum[j] += w;
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sum[j] += val * w;
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val = ksptr3[j];
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w = space_weight[k+3] * color_weight[std::abs(val - rval)];
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wsum[j] += w;
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sum[j] += val * w;
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#endif
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}
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}
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for(; k < maxk; k++)
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{
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const uchar* ksptr = sptr + space_ofs[k];
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j = 0;
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@ -126,7 +203,232 @@ public:
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float *sum_g = sum_b + alignSize(size.width, CV_SIMD_WIDTH);
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float *sum_r = sum_g + alignSize(size.width, CV_SIMD_WIDTH);
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float *wsum = sum_r + alignSize(size.width, CV_SIMD_WIDTH);
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for(k = 0; k < maxk; k++ )
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k = 0;
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for(; k <= maxk-4; k+=4)
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{
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const uchar* ksptr0 = sptr + space_ofs[k];
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const uchar* ksptr1 = sptr + space_ofs[k+1];
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const uchar* ksptr2 = sptr + space_ofs[k+2];
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const uchar* ksptr3 = sptr + space_ofs[k+3];
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const uchar* rsptr = sptr;
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j = 0;
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#if CV_SIMD
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v_float32 kweight0 = vx_setall_f32(space_weight[k]);
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v_float32 kweight1 = vx_setall_f32(space_weight[k+1]);
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v_float32 kweight2 = vx_setall_f32(space_weight[k+2]);
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v_float32 kweight3 = vx_setall_f32(space_weight[k+3]);
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for (; j <= size.width - v_uint8::nlanes; j += v_uint8::nlanes, rsptr += 3*v_uint8::nlanes,
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ksptr0 += 3*v_uint8::nlanes, ksptr1 += 3*v_uint8::nlanes, ksptr2 += 3*v_uint8::nlanes, ksptr3 += 3*v_uint8::nlanes)
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{
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v_uint8 kb, kg, kr, rb, rg, rr;
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v_load_deinterleave(rsptr, rb, rg, rr);
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v_load_deinterleave(ksptr0, kb, kg, kr);
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v_uint16 val0, val1, val2, val3, val4;
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v_expand(v_absdiff(kb, rb), val0, val1);
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v_expand(v_absdiff(kg, rg), val2, val3);
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val0 += val2; val1 += val3;
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v_expand(v_absdiff(kr, rr), val2, val3);
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val0 += val2; val1 += val3;
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v_uint32 vall, valh;
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v_expand(val0, vall, valh);
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v_float32 w0 = kweight0 * v_lut(color_weight, v_reinterpret_as_s32(vall));
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v_float32 w1 = kweight0 * v_lut(color_weight, v_reinterpret_as_s32(valh));
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v_store_aligned(wsum + j, w0 + vx_load_aligned(wsum + j));
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v_store_aligned(wsum + j + v_float32::nlanes, w1 + vx_load_aligned(wsum + j + v_float32::nlanes));
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v_expand(kb, val0, val2);
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v_expand(val0, vall, valh);
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v_store_aligned(sum_b + j , v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_b + j)));
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v_store_aligned(sum_b + j + v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_b + j + v_float32::nlanes)));
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v_expand(kg, val0, val3);
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v_expand(val0, vall, valh);
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v_store_aligned(sum_g + j , v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_g + j)));
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v_store_aligned(sum_g + j + v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_g + j + v_float32::nlanes)));
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v_expand(kr, val0, val4);
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v_expand(val0, vall, valh);
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v_store_aligned(sum_r + j , v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_r + j)));
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v_store_aligned(sum_r + j + v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_r + j + v_float32::nlanes)));
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v_expand(val1, vall, valh);
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w0 = kweight0 * v_lut(color_weight, v_reinterpret_as_s32(vall));
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w1 = kweight0 * v_lut(color_weight, v_reinterpret_as_s32(valh));
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v_store_aligned(wsum + j + 2 * v_float32::nlanes, w0 + vx_load_aligned(wsum + j + 2 * v_float32::nlanes));
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v_store_aligned(wsum + j + 3 * v_float32::nlanes, w1 + vx_load_aligned(wsum + j + 3 * v_float32::nlanes));
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v_expand(val2, vall, valh);
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v_store_aligned(sum_b + j + 2 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_b + j + 2 * v_float32::nlanes)));
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v_store_aligned(sum_b + j + 3 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_b + j + 3 * v_float32::nlanes)));
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v_expand(val3, vall, valh);
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v_store_aligned(sum_g + j + 2 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_g + j + 2 * v_float32::nlanes)));
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v_store_aligned(sum_g + j + 3 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_g + j + 3 * v_float32::nlanes)));
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v_expand(val4, vall, valh);
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v_store_aligned(sum_r + j + 2*v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_r + j + 2*v_float32::nlanes)));
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v_store_aligned(sum_r + j + 3*v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_r + j + 3*v_float32::nlanes)));
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v_load_deinterleave(ksptr1, kb, kg, kr);
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v_expand(v_absdiff(kb, rb), val0, val1);
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v_expand(v_absdiff(kg, rg), val2, val3);
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val0 += val2; val1 += val3;
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v_expand(v_absdiff(kr, rr), val2, val3);
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val0 += val2; val1 += val3;
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v_expand(val0, vall, valh);
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w0 = kweight1 * v_lut(color_weight, v_reinterpret_as_s32(vall));
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w1 = kweight1 * v_lut(color_weight, v_reinterpret_as_s32(valh));
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v_store_aligned(wsum + j, w0 + vx_load_aligned(wsum + j));
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v_store_aligned(wsum + j + v_float32::nlanes, w1 + vx_load_aligned(wsum + j + v_float32::nlanes));
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v_expand(kb, val0, val2);
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v_expand(val0, vall, valh);
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v_store_aligned(sum_b + j, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_b + j)));
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v_store_aligned(sum_b + j + v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_b + j + v_float32::nlanes)));
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v_expand(kg, val0, val3);
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v_expand(val0, vall, valh);
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v_store_aligned(sum_g + j, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_g + j)));
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v_store_aligned(sum_g + j + v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_g + j + v_float32::nlanes)));
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v_expand(kr, val0, val4);
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v_expand(val0, vall, valh);
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v_store_aligned(sum_r + j, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_r + j)));
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v_store_aligned(sum_r + j + v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_r + j + v_float32::nlanes)));
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v_expand(val1, vall, valh);
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w0 = kweight1 * v_lut(color_weight, v_reinterpret_as_s32(vall));
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w1 = kweight1 * v_lut(color_weight, v_reinterpret_as_s32(valh));
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v_store_aligned(wsum + j + 2 * v_float32::nlanes, w0 + vx_load_aligned(wsum + j + 2 * v_float32::nlanes));
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v_store_aligned(wsum + j + 3 * v_float32::nlanes, w1 + vx_load_aligned(wsum + j + 3 * v_float32::nlanes));
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v_expand(val2, vall, valh);
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v_store_aligned(sum_b + j + 2 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_b + j + 2 * v_float32::nlanes)));
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v_store_aligned(sum_b + j + 3 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_b + j + 3 * v_float32::nlanes)));
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v_expand(val3, vall, valh);
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v_store_aligned(sum_g + j + 2 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_g + j + 2 * v_float32::nlanes)));
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v_store_aligned(sum_g + j + 3 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_g + j + 3 * v_float32::nlanes)));
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v_expand(val4, vall, valh);
|
||||
v_store_aligned(sum_r + j + 2 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_r + j + 2 * v_float32::nlanes)));
|
||||
v_store_aligned(sum_r + j + 3 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_r + j + 3 * v_float32::nlanes)));
|
||||
|
||||
v_load_deinterleave(ksptr2, kb, kg, kr);
|
||||
v_expand(v_absdiff(kb, rb), val0, val1);
|
||||
v_expand(v_absdiff(kg, rg), val2, val3);
|
||||
val0 += val2; val1 += val3;
|
||||
v_expand(v_absdiff(kr, rr), val2, val3);
|
||||
val0 += val2; val1 += val3;
|
||||
|
||||
v_expand(val0, vall, valh);
|
||||
w0 = kweight2 * v_lut(color_weight, v_reinterpret_as_s32(vall));
|
||||
w1 = kweight2 * v_lut(color_weight, v_reinterpret_as_s32(valh));
|
||||
v_store_aligned(wsum + j, w0 + vx_load_aligned(wsum + j));
|
||||
v_store_aligned(wsum + j + v_float32::nlanes, w1 + vx_load_aligned(wsum + j + v_float32::nlanes));
|
||||
v_expand(kb, val0, val2);
|
||||
v_expand(val0, vall, valh);
|
||||
v_store_aligned(sum_b + j, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_b + j)));
|
||||
v_store_aligned(sum_b + j + v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_b + j + v_float32::nlanes)));
|
||||
v_expand(kg, val0, val3);
|
||||
v_expand(val0, vall, valh);
|
||||
v_store_aligned(sum_g + j, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_g + j)));
|
||||
v_store_aligned(sum_g + j + v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_g + j + v_float32::nlanes)));
|
||||
v_expand(kr, val0, val4);
|
||||
v_expand(val0, vall, valh);
|
||||
v_store_aligned(sum_r + j, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_r + j)));
|
||||
v_store_aligned(sum_r + j + v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_r + j + v_float32::nlanes)));
|
||||
|
||||
v_expand(val1, vall, valh);
|
||||
w0 = kweight2 * v_lut(color_weight, v_reinterpret_as_s32(vall));
|
||||
w1 = kweight2 * v_lut(color_weight, v_reinterpret_as_s32(valh));
|
||||
v_store_aligned(wsum + j + 2 * v_float32::nlanes, w0 + vx_load_aligned(wsum + j + 2 * v_float32::nlanes));
|
||||
v_store_aligned(wsum + j + 3 * v_float32::nlanes, w1 + vx_load_aligned(wsum + j + 3 * v_float32::nlanes));
|
||||
v_expand(val2, vall, valh);
|
||||
v_store_aligned(sum_b + j + 2 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_b + j + 2 * v_float32::nlanes)));
|
||||
v_store_aligned(sum_b + j + 3 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_b + j + 3 * v_float32::nlanes)));
|
||||
v_expand(val3, vall, valh);
|
||||
v_store_aligned(sum_g + j + 2 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_g + j + 2 * v_float32::nlanes)));
|
||||
v_store_aligned(sum_g + j + 3 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_g + j + 3 * v_float32::nlanes)));
|
||||
v_expand(val4, vall, valh);
|
||||
v_store_aligned(sum_r + j + 2 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_r + j + 2 * v_float32::nlanes)));
|
||||
v_store_aligned(sum_r + j + 3 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_r + j + 3 * v_float32::nlanes)));
|
||||
|
||||
v_load_deinterleave(ksptr3, kb, kg, kr);
|
||||
v_expand(v_absdiff(kb, rb), val0, val1);
|
||||
v_expand(v_absdiff(kg, rg), val2, val3);
|
||||
val0 += val2; val1 += val3;
|
||||
v_expand(v_absdiff(kr, rr), val2, val3);
|
||||
val0 += val2; val1 += val3;
|
||||
|
||||
v_expand(val0, vall, valh);
|
||||
w0 = kweight3 * v_lut(color_weight, v_reinterpret_as_s32(vall));
|
||||
w1 = kweight3 * v_lut(color_weight, v_reinterpret_as_s32(valh));
|
||||
v_store_aligned(wsum + j, w0 + vx_load_aligned(wsum + j));
|
||||
v_store_aligned(wsum + j + v_float32::nlanes, w1 + vx_load_aligned(wsum + j + v_float32::nlanes));
|
||||
v_expand(kb, val0, val2);
|
||||
v_expand(val0, vall, valh);
|
||||
v_store_aligned(sum_b + j, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_b + j)));
|
||||
v_store_aligned(sum_b + j + v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_b + j + v_float32::nlanes)));
|
||||
v_expand(kg, val0, val3);
|
||||
v_expand(val0, vall, valh);
|
||||
v_store_aligned(sum_g + j, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_g + j)));
|
||||
v_store_aligned(sum_g + j + v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_g + j + v_float32::nlanes)));
|
||||
v_expand(kr, val0, val4);
|
||||
v_expand(val0, vall, valh);
|
||||
v_store_aligned(sum_r + j, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_r + j)));
|
||||
v_store_aligned(sum_r + j + v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_r + j + v_float32::nlanes)));
|
||||
|
||||
v_expand(val1, vall, valh);
|
||||
w0 = kweight3 * v_lut(color_weight, v_reinterpret_as_s32(vall));
|
||||
w1 = kweight3 * v_lut(color_weight, v_reinterpret_as_s32(valh));
|
||||
v_store_aligned(wsum + j + 2 * v_float32::nlanes, w0 + vx_load_aligned(wsum + j + 2 * v_float32::nlanes));
|
||||
v_store_aligned(wsum + j + 3 * v_float32::nlanes, w1 + vx_load_aligned(wsum + j + 3 * v_float32::nlanes));
|
||||
v_expand(val2, vall, valh);
|
||||
v_store_aligned(sum_b + j + 2 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_b + j + 2 * v_float32::nlanes)));
|
||||
v_store_aligned(sum_b + j + 3 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_b + j + 3 * v_float32::nlanes)));
|
||||
v_expand(val3, vall, valh);
|
||||
v_store_aligned(sum_g + j + 2 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_g + j + 2 * v_float32::nlanes)));
|
||||
v_store_aligned(sum_g + j + 3 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_g + j + 3 * v_float32::nlanes)));
|
||||
v_expand(val4, vall, valh);
|
||||
v_store_aligned(sum_r + j + 2 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(vall)), w0, vx_load_aligned(sum_r + j + 2 * v_float32::nlanes)));
|
||||
v_store_aligned(sum_r + j + 3 * v_float32::nlanes, v_muladd(v_cvt_f32(v_reinterpret_as_s32(valh)), w1, vx_load_aligned(sum_r + j + 3 * v_float32::nlanes)));
|
||||
}
|
||||
#endif
|
||||
#if CV_SIMD128
|
||||
v_float32x4 kweight4 = v_load(space_weight + k);
|
||||
#endif
|
||||
for(; j < size.width; j++, rsptr += 3, ksptr0 += 3, ksptr1 += 3, ksptr2 += 3, ksptr3 += 3)
|
||||
{
|
||||
#if CV_SIMD128
|
||||
v_uint32x4 rb = v_setall_u32(rsptr[0]);
|
||||
v_uint32x4 rg = v_setall_u32(rsptr[1]);
|
||||
v_uint32x4 rr = v_setall_u32(rsptr[2]);
|
||||
v_uint32x4 b(ksptr0[0], ksptr1[0], ksptr2[0], ksptr3[0]);
|
||||
v_uint32x4 g(ksptr0[1], ksptr1[1], ksptr2[1], ksptr3[1]);
|
||||
v_uint32x4 r(ksptr0[2], ksptr1[2], ksptr2[2], ksptr3[2]);
|
||||
v_float32x4 w = kweight4 * v_lut(color_weight, v_reinterpret_as_s32(v_absdiff(b, rb) + v_absdiff(g, rg) + v_absdiff(r, rr)));
|
||||
wsum[j] += v_reduce_sum(w);
|
||||
sum_b[j] += v_reduce_sum(v_cvt_f32(v_reinterpret_as_s32(b)) * w);
|
||||
sum_g[j] += v_reduce_sum(v_cvt_f32(v_reinterpret_as_s32(g)) * w);
|
||||
sum_r[j] += v_reduce_sum(v_cvt_f32(v_reinterpret_as_s32(r)) * w);
|
||||
#else
|
||||
int rb = rsptr[0], rg = rsptr[1], rr = rsptr[2];
|
||||
|
||||
int b = ksptr0[0], g = ksptr0[1], r = ksptr0[2];
|
||||
float w = space_weight[k]*color_weight[std::abs(b - rb) + std::abs(g - rg) + std::abs(r - rr)];
|
||||
wsum[j] += w;
|
||||
sum_b[j] += b*w; sum_g[j] += g*w; sum_r[j] += r*w;
|
||||
|
||||
b = ksptr1[0]; g = ksptr1[1]; r = ksptr1[2];
|
||||
w = space_weight[k+1] * color_weight[std::abs(b - rb) + std::abs(g - rg) + std::abs(r - rr)];
|
||||
wsum[j] += w;
|
||||
sum_b[j] += b*w; sum_g[j] += g*w; sum_r[j] += r*w;
|
||||
|
||||
b = ksptr2[0]; g = ksptr2[1]; r = ksptr2[2];
|
||||
w = space_weight[k+2] * color_weight[std::abs(b - rb) + std::abs(g - rg) + std::abs(r - rr)];
|
||||
wsum[j] += w;
|
||||
sum_b[j] += b*w; sum_g[j] += g*w; sum_r[j] += r*w;
|
||||
|
||||
b = ksptr3[0]; g = ksptr3[1]; r = ksptr3[2];
|
||||
w = space_weight[k+3] * color_weight[std::abs(b - rb) + std::abs(g - rg) + std::abs(r - rr)];
|
||||
wsum[j] += w;
|
||||
sum_b[j] += b*w; sum_g[j] += g*w; sum_r[j] += r*w;
|
||||
#endif
|
||||
}
|
||||
}
|
||||
for(; k < maxk; k++)
|
||||
{
|
||||
const uchar* ksptr = sptr + space_ofs[k];
|
||||
const uchar* rsptr = sptr;
|
||||
@ -421,7 +723,130 @@ public:
|
||||
v_float32 v_one = vx_setall_f32(1.f);
|
||||
v_float32 sindex = vx_setall_f32(scale_index);
|
||||
#endif
|
||||
for( k = 0; k < maxk; k++ )
|
||||
k = 0;
|
||||
for(; k <= maxk - 4; k+=4)
|
||||
{
|
||||
const float* ksptr0 = sptr + space_ofs[k];
|
||||
const float* ksptr1 = sptr + space_ofs[k + 1];
|
||||
const float* ksptr2 = sptr + space_ofs[k + 2];
|
||||
const float* ksptr3 = sptr + space_ofs[k + 3];
|
||||
j = 0;
|
||||
#if CV_SIMD
|
||||
v_float32 kweight0 = vx_setall_f32(space_weight[k]);
|
||||
v_float32 kweight1 = vx_setall_f32(space_weight[k+1]);
|
||||
v_float32 kweight2 = vx_setall_f32(space_weight[k+2]);
|
||||
v_float32 kweight3 = vx_setall_f32(space_weight[k+3]);
|
||||
for (; j <= size.width - v_float32::nlanes; j += v_float32::nlanes)
|
||||
{
|
||||
v_float32 rval = vx_load(sptr + j);
|
||||
|
||||
v_float32 val = vx_load(ksptr0 + j);
|
||||
v_float32 knan = v_not_nan(val);
|
||||
v_float32 alpha = (v_absdiff(val, rval) * sindex) & v_not_nan(rval) & knan;
|
||||
v_int32 idx = v_trunc(alpha);
|
||||
alpha -= v_cvt_f32(idx);
|
||||
v_float32 w = (kweight0 * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one-alpha))) & knan;
|
||||
v_float32 v_wsum = vx_load_aligned(wsum + j) + w;
|
||||
v_float32 v_sum = v_muladd(val & knan, w, vx_load_aligned(sum + j));
|
||||
|
||||
val = vx_load(ksptr1 + j);
|
||||
knan = v_not_nan(val);
|
||||
alpha = (v_absdiff(val, rval) * sindex) & v_not_nan(rval) & knan;
|
||||
idx = v_trunc(alpha);
|
||||
alpha -= v_cvt_f32(idx);
|
||||
w = (kweight1 * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one - alpha))) & knan;
|
||||
v_wsum += w;
|
||||
v_sum = v_muladd(val & knan, w, v_sum);
|
||||
|
||||
val = vx_load(ksptr2 + j);
|
||||
knan = v_not_nan(val);
|
||||
alpha = (v_absdiff(val, rval) * sindex) & v_not_nan(rval) & knan;
|
||||
idx = v_trunc(alpha);
|
||||
alpha -= v_cvt_f32(idx);
|
||||
w = (kweight2 * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one - alpha))) & knan;
|
||||
v_wsum += w;
|
||||
v_sum = v_muladd(val & knan, w, v_sum);
|
||||
|
||||
val = vx_load(ksptr3 + j);
|
||||
knan = v_not_nan(val);
|
||||
alpha = (v_absdiff(val, rval) * sindex) & v_not_nan(rval) & knan;
|
||||
idx = v_trunc(alpha);
|
||||
alpha -= v_cvt_f32(idx);
|
||||
w = (kweight3 * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one - alpha))) & knan;
|
||||
v_wsum += w;
|
||||
v_sum = v_muladd(val & knan, w, v_sum);
|
||||
|
||||
v_store_aligned(wsum + j, v_wsum);
|
||||
v_store_aligned(sum + j, v_sum);
|
||||
}
|
||||
#endif
|
||||
#if CV_SIMD128
|
||||
v_float32x4 v_one4 = v_setall_f32(1.f);
|
||||
v_float32x4 sindex4 = v_setall_f32(scale_index);
|
||||
v_float32x4 kweight4 = v_load(space_weight + k);
|
||||
#endif
|
||||
for (; j < size.width; j++)
|
||||
{
|
||||
#if CV_SIMD128
|
||||
v_float32x4 rval = v_setall_f32(sptr[j]);
|
||||
v_float32x4 val(ksptr0[j], ksptr1[j], ksptr2[j], ksptr3[j]);
|
||||
v_float32x4 knan = v_not_nan(val);
|
||||
v_float32x4 alpha = (v_absdiff(val, rval) * sindex4) & v_not_nan(rval) & knan;
|
||||
v_int32x4 idx = v_trunc(alpha);
|
||||
alpha -= v_cvt_f32(idx);
|
||||
v_float32x4 w = (kweight4 * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one4 - alpha))) & knan;
|
||||
wsum[j] += v_reduce_sum(w);
|
||||
sum[j] += v_reduce_sum((val & knan) * w);
|
||||
#else
|
||||
float rval = sptr[j];
|
||||
|
||||
float val = ksptr0[j];
|
||||
float alpha = std::abs(val - rval) * scale_index;
|
||||
int idx = cvFloor(alpha);
|
||||
alpha -= idx;
|
||||
if (!cvIsNaN(val))
|
||||
{
|
||||
float w = space_weight[k] * (cvIsNaN(rval) ? 1.f : (expLUT[idx] + alpha*(expLUT[idx + 1] - expLUT[idx])));
|
||||
wsum[j] += w;
|
||||
sum[j] += val * w;
|
||||
}
|
||||
|
||||
val = ksptr1[j];
|
||||
alpha = std::abs(val - rval) * scale_index;
|
||||
idx = cvFloor(alpha);
|
||||
alpha -= idx;
|
||||
if (!cvIsNaN(val))
|
||||
{
|
||||
float w = space_weight[k+1] * (cvIsNaN(rval) ? 1.f : (expLUT[idx] + alpha*(expLUT[idx + 1] - expLUT[idx])));
|
||||
wsum[j] += w;
|
||||
sum[j] += val * w;
|
||||
}
|
||||
|
||||
val = ksptr2[j];
|
||||
alpha = std::abs(val - rval) * scale_index;
|
||||
idx = cvFloor(alpha);
|
||||
alpha -= idx;
|
||||
if (!cvIsNaN(val))
|
||||
{
|
||||
float w = space_weight[k+2] * (cvIsNaN(rval) ? 1.f : (expLUT[idx] + alpha*(expLUT[idx + 1] - expLUT[idx])));
|
||||
wsum[j] += w;
|
||||
sum[j] += val * w;
|
||||
}
|
||||
|
||||
val = ksptr3[j];
|
||||
alpha = std::abs(val - rval) * scale_index;
|
||||
idx = cvFloor(alpha);
|
||||
alpha -= idx;
|
||||
if (!cvIsNaN(val))
|
||||
{
|
||||
float w = space_weight[k+3] * (cvIsNaN(rval) ? 1.f : (expLUT[idx] + alpha*(expLUT[idx + 1] - expLUT[idx])));
|
||||
wsum[j] += w;
|
||||
sum[j] += val * w;
|
||||
}
|
||||
#endif
|
||||
}
|
||||
}
|
||||
for(; k < maxk; k++)
|
||||
{
|
||||
const float* ksptr = sptr + space_ofs[k];
|
||||
j = 0;
|
||||
@ -430,36 +855,44 @@ public:
|
||||
for (; j <= size.width - v_float32::nlanes; j += v_float32::nlanes)
|
||||
{
|
||||
v_float32 val = vx_load(ksptr + j);
|
||||
|
||||
v_float32 alpha = v_absdiff(val, vx_load(sptr + j)) * sindex;
|
||||
v_float32 rval = vx_load(sptr + j);
|
||||
v_float32 knan = v_not_nan(val);
|
||||
v_float32 alpha = (v_absdiff(val, rval) * sindex) & v_not_nan(rval) & knan;
|
||||
v_int32 idx = v_trunc(alpha);
|
||||
alpha -= v_cvt_f32(idx);
|
||||
|
||||
v_float32 w = kweight * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one-alpha));
|
||||
v_float32 w = (kweight * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one-alpha))) & knan;
|
||||
v_store_aligned(wsum + j, vx_load_aligned(wsum + j) + w);
|
||||
v_store_aligned(sum + j, v_muladd(val, w, vx_load_aligned(sum + j)));
|
||||
v_store_aligned(sum + j, v_muladd(val & knan, w, vx_load_aligned(sum + j)));
|
||||
}
|
||||
#endif
|
||||
for (; j < size.width; j++)
|
||||
{
|
||||
float val = ksptr[j];
|
||||
float alpha = std::abs(val - sptr[j]) * scale_index;
|
||||
float rval = sptr[j];
|
||||
float alpha = std::abs(val - rval) * scale_index;
|
||||
int idx = cvFloor(alpha);
|
||||
alpha -= idx;
|
||||
float w = space_weight[k] * (expLUT[idx] + alpha*(expLUT[idx+1] - expLUT[idx]));
|
||||
wsum[j] += w;
|
||||
sum[j] += val * w;
|
||||
if (!cvIsNaN(val))
|
||||
{
|
||||
float w = space_weight[k] * (cvIsNaN(rval) ? 1.f : (expLUT[idx] + alpha*(expLUT[idx + 1] - expLUT[idx])));
|
||||
wsum[j] += w;
|
||||
sum[j] += val * w;
|
||||
}
|
||||
}
|
||||
}
|
||||
j = 0;
|
||||
#if CV_SIMD
|
||||
for (; j <= size.width - v_float32::nlanes; j += v_float32::nlanes)
|
||||
v_store(dptr + j, vx_load_aligned(sum + j) / vx_load_aligned(wsum + j));
|
||||
{
|
||||
v_float32 v_val = vx_load(sptr + j);
|
||||
v_store(dptr + j, (vx_load_aligned(sum + j) + (v_val & v_not_nan(v_val))) / (vx_load_aligned(wsum + j) + (v_one & v_not_nan(v_val))));
|
||||
}
|
||||
#endif
|
||||
for (; j < size.width; j++)
|
||||
{
|
||||
CV_DbgAssert(fabs(wsum[j]) > 0);
|
||||
dptr[j] = sum[j] / wsum[j];
|
||||
CV_DbgAssert(fabs(wsum[j]) >= 0);
|
||||
dptr[j] = cvIsNaN(sptr[j]) ? sum[j] / wsum[j] : (sum[j] + sptr[j]) / (wsum[j] + 1.f);
|
||||
}
|
||||
}
|
||||
else
|
||||
@ -475,7 +908,162 @@ public:
|
||||
v_float32 v_one = vx_setall_f32(1.f);
|
||||
v_float32 sindex = vx_setall_f32(scale_index);
|
||||
#endif
|
||||
for (k = 0; k < maxk; k++)
|
||||
k = 0;
|
||||
for (; k <= maxk-4; k+=4)
|
||||
{
|
||||
const float* ksptr0 = sptr + space_ofs[k];
|
||||
const float* ksptr1 = sptr + space_ofs[k+1];
|
||||
const float* ksptr2 = sptr + space_ofs[k+2];
|
||||
const float* ksptr3 = sptr + space_ofs[k+3];
|
||||
const float* rsptr = sptr;
|
||||
j = 0;
|
||||
#if CV_SIMD
|
||||
v_float32 kweight0 = vx_setall_f32(space_weight[k]);
|
||||
v_float32 kweight1 = vx_setall_f32(space_weight[k+1]);
|
||||
v_float32 kweight2 = vx_setall_f32(space_weight[k+2]);
|
||||
v_float32 kweight3 = vx_setall_f32(space_weight[k+3]);
|
||||
for (; j <= size.width - v_float32::nlanes; j += v_float32::nlanes, rsptr += 3 * v_float32::nlanes,
|
||||
ksptr0 += 3 * v_float32::nlanes, ksptr1 += 3 * v_float32::nlanes, ksptr2 += 3 * v_float32::nlanes, ksptr3 += 3 * v_float32::nlanes)
|
||||
{
|
||||
v_float32 kb, kg, kr, rb, rg, rr;
|
||||
v_load_deinterleave(rsptr, rb, rg, rr);
|
||||
|
||||
v_load_deinterleave(ksptr0, kb, kg, kr);
|
||||
v_float32 knan = v_not_nan(kb) & v_not_nan(kg) & v_not_nan(kr);
|
||||
v_float32 alpha = ((v_absdiff(kb, rb) + v_absdiff(kg, rg) + v_absdiff(kr, rr)) * sindex) & v_not_nan(rb) & v_not_nan(rg) & v_not_nan(rr) & knan;
|
||||
v_int32 idx = v_trunc(alpha);
|
||||
alpha -= v_cvt_f32(idx);
|
||||
v_float32 w = (kweight0 * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one - alpha))) & knan;
|
||||
v_float32 v_wsum = vx_load_aligned(wsum + j) + w;
|
||||
v_float32 v_sum_b = v_muladd(kb & knan, w, vx_load_aligned(sum_b + j));
|
||||
v_float32 v_sum_g = v_muladd(kg & knan, w, vx_load_aligned(sum_g + j));
|
||||
v_float32 v_sum_r = v_muladd(kr & knan, w, vx_load_aligned(sum_r + j));
|
||||
|
||||
v_load_deinterleave(ksptr1, kb, kg, kr);
|
||||
knan = v_not_nan(kb) & v_not_nan(kg) & v_not_nan(kr);
|
||||
alpha = ((v_absdiff(kb, rb) + v_absdiff(kg, rg) + v_absdiff(kr, rr)) * sindex) & v_not_nan(rb) & v_not_nan(rg) & v_not_nan(rr) & knan;
|
||||
idx = v_trunc(alpha);
|
||||
alpha -= v_cvt_f32(idx);
|
||||
w = (kweight1 * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one - alpha))) & knan;
|
||||
v_wsum += w;
|
||||
v_sum_b = v_muladd(kb & knan, w, v_sum_b);
|
||||
v_sum_g = v_muladd(kg & knan, w, v_sum_g);
|
||||
v_sum_r = v_muladd(kr & knan, w, v_sum_r);
|
||||
|
||||
v_load_deinterleave(ksptr2, kb, kg, kr);
|
||||
knan = v_not_nan(kb) & v_not_nan(kg) & v_not_nan(kr);
|
||||
alpha = ((v_absdiff(kb, rb) + v_absdiff(kg, rg) + v_absdiff(kr, rr)) * sindex) & v_not_nan(rb) & v_not_nan(rg) & v_not_nan(rr) & knan;
|
||||
idx = v_trunc(alpha);
|
||||
alpha -= v_cvt_f32(idx);
|
||||
w = (kweight2 * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one - alpha))) & knan;
|
||||
v_wsum += w;
|
||||
v_sum_b = v_muladd(kb & knan, w, v_sum_b);
|
||||
v_sum_g = v_muladd(kg & knan, w, v_sum_g);
|
||||
v_sum_r = v_muladd(kr & knan, w, v_sum_r);
|
||||
|
||||
v_load_deinterleave(ksptr3, kb, kg, kr);
|
||||
knan = v_not_nan(kb) & v_not_nan(kg) & v_not_nan(kr);
|
||||
alpha = ((v_absdiff(kb, rb) + v_absdiff(kg, rg) + v_absdiff(kr, rr)) * sindex) & v_not_nan(rb) & v_not_nan(rg) & v_not_nan(rr) & knan;
|
||||
idx = v_trunc(alpha);
|
||||
alpha -= v_cvt_f32(idx);
|
||||
w = (kweight3 * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one - alpha))) & knan;
|
||||
v_wsum += w;
|
||||
v_sum_b = v_muladd(kb & knan, w, v_sum_b);
|
||||
v_sum_g = v_muladd(kg & knan, w, v_sum_g);
|
||||
v_sum_r = v_muladd(kr & knan, w, v_sum_r);
|
||||
|
||||
v_store_aligned(wsum + j, v_wsum);
|
||||
v_store_aligned(sum_b + j, v_sum_b);
|
||||
v_store_aligned(sum_g + j, v_sum_g);
|
||||
v_store_aligned(sum_r + j, v_sum_r);
|
||||
}
|
||||
#endif
|
||||
#if CV_SIMD128
|
||||
v_float32x4 v_one4 = v_setall_f32(1.f);
|
||||
v_float32x4 sindex4 = v_setall_f32(scale_index);
|
||||
v_float32x4 kweight4 = v_load(space_weight + k);
|
||||
#endif
|
||||
for (; j < size.width; j++, rsptr += 3, ksptr0 += 3, ksptr1 += 3, ksptr2 += 3, ksptr3 += 3)
|
||||
{
|
||||
#if CV_SIMD128
|
||||
v_float32x4 rb = v_setall_f32(rsptr[0]);
|
||||
v_float32x4 rg = v_setall_f32(rsptr[1]);
|
||||
v_float32x4 rr = v_setall_f32(rsptr[2]);
|
||||
v_float32x4 kb(ksptr0[0], ksptr1[0], ksptr2[0], ksptr3[0]);
|
||||
v_float32x4 kg(ksptr0[1], ksptr1[1], ksptr2[1], ksptr3[1]);
|
||||
v_float32x4 kr(ksptr0[2], ksptr1[2], ksptr2[2], ksptr3[2]);
|
||||
v_float32x4 knan = v_not_nan(kb) & v_not_nan(kg) & v_not_nan(kr);
|
||||
v_float32x4 alpha = ((v_absdiff(kb, rb) + v_absdiff(kg, rg) + v_absdiff(kr, rr)) * sindex4) & v_not_nan(rb) & v_not_nan(rg) & v_not_nan(rr) & knan;
|
||||
v_int32x4 idx = v_trunc(alpha);
|
||||
alpha -= v_cvt_f32(idx);
|
||||
v_float32x4 w = (kweight4 * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one4 - alpha))) & knan;
|
||||
wsum[j] += v_reduce_sum(w);
|
||||
sum_b[j] += v_reduce_sum((kb & knan) * w);
|
||||
sum_g[j] += v_reduce_sum((kg & knan) * w);
|
||||
sum_r[j] += v_reduce_sum((kr & knan) * w);
|
||||
#else
|
||||
float rb = rsptr[0], rg = rsptr[1], rr = rsptr[2];
|
||||
bool r_NAN = cvIsNaN(rb) || cvIsNaN(rg) || cvIsNaN(rr);
|
||||
|
||||
float b = ksptr0[0], g = ksptr0[1], r = ksptr0[2];
|
||||
bool v_NAN = cvIsNaN(b) || cvIsNaN(g) || cvIsNaN(r);
|
||||
float alpha = (std::abs(b - rb) + std::abs(g - rg) + std::abs(r - rr)) * scale_index;
|
||||
int idx = cvFloor(alpha);
|
||||
alpha -= idx;
|
||||
if (!v_NAN)
|
||||
{
|
||||
float w = space_weight[k] * (r_NAN ? 1.f : (expLUT[idx] + alpha*(expLUT[idx + 1] - expLUT[idx])));
|
||||
wsum[j] += w;
|
||||
sum_b[j] += b*w;
|
||||
sum_g[j] += g*w;
|
||||
sum_r[j] += r*w;
|
||||
}
|
||||
|
||||
b = ksptr1[0]; g = ksptr1[1]; r = ksptr1[2];
|
||||
v_NAN = cvIsNaN(b) || cvIsNaN(g) || cvIsNaN(r);
|
||||
alpha = (std::abs(b - rb) + std::abs(g - rg) + std::abs(r - rr)) * scale_index;
|
||||
idx = cvFloor(alpha);
|
||||
alpha -= idx;
|
||||
if (!v_NAN)
|
||||
{
|
||||
float w = space_weight[k+1] * (r_NAN ? 1.f : (expLUT[idx] + alpha*(expLUT[idx + 1] - expLUT[idx])));
|
||||
wsum[j] += w;
|
||||
sum_b[j] += b*w;
|
||||
sum_g[j] += g*w;
|
||||
sum_r[j] += r*w;
|
||||
}
|
||||
|
||||
b = ksptr2[0]; g = ksptr2[1]; r = ksptr2[2];
|
||||
v_NAN = cvIsNaN(b) || cvIsNaN(g) || cvIsNaN(r);
|
||||
alpha = (std::abs(b - rb) + std::abs(g - rg) + std::abs(r - rr)) * scale_index;
|
||||
idx = cvFloor(alpha);
|
||||
alpha -= idx;
|
||||
if (!v_NAN)
|
||||
{
|
||||
float w = space_weight[k+2] * (r_NAN ? 1.f : (expLUT[idx] + alpha*(expLUT[idx + 1] - expLUT[idx])));
|
||||
wsum[j] += w;
|
||||
sum_b[j] += b*w;
|
||||
sum_g[j] += g*w;
|
||||
sum_r[j] += r*w;
|
||||
}
|
||||
|
||||
b = ksptr3[0]; g = ksptr3[1]; r = ksptr3[2];
|
||||
v_NAN = cvIsNaN(b) || cvIsNaN(g) || cvIsNaN(r);
|
||||
alpha = (std::abs(b - rb) + std::abs(g - rg) + std::abs(r - rr)) * scale_index;
|
||||
idx = cvFloor(alpha);
|
||||
alpha -= idx;
|
||||
if (!v_NAN)
|
||||
{
|
||||
float w = space_weight[k+3] * (r_NAN ? 1.f : (expLUT[idx] + alpha*(expLUT[idx + 1] - expLUT[idx])));
|
||||
wsum[j] += w;
|
||||
sum_b[j] += b*w;
|
||||
sum_g[j] += g*w;
|
||||
sum_r[j] += r*w;
|
||||
}
|
||||
#endif
|
||||
}
|
||||
}
|
||||
for (; k < maxk; k++)
|
||||
{
|
||||
const float* ksptr = sptr + space_ofs[k];
|
||||
const float* rsptr = sptr;
|
||||
@ -488,45 +1076,68 @@ public:
|
||||
v_load_deinterleave(ksptr, kb, kg, kr);
|
||||
v_load_deinterleave(rsptr, rb, rg, rr);
|
||||
|
||||
v_float32 alpha = (v_absdiff(kb, rb) + v_absdiff(kg, rg) + v_absdiff(kr, rr)) * sindex;
|
||||
v_float32 knan = v_not_nan(kb) & v_not_nan(kg) & v_not_nan(kr);
|
||||
v_float32 alpha = ((v_absdiff(kb, rb) + v_absdiff(kg, rg) + v_absdiff(kr, rr)) * sindex) & v_not_nan(rb) & v_not_nan(rg) & v_not_nan(rr) & knan;
|
||||
v_int32 idx = v_trunc(alpha);
|
||||
alpha -= v_cvt_f32(idx);
|
||||
|
||||
v_float32 w = kweight * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one - alpha));
|
||||
v_float32 w = (kweight * v_muladd(v_lut(expLUT + 1, idx), alpha, v_lut(expLUT, idx) * (v_one - alpha))) & knan;
|
||||
v_store_aligned(wsum + j, vx_load_aligned(wsum + j) + w);
|
||||
v_store_aligned(sum_b + j, v_muladd(kb, w, vx_load_aligned(sum_b + j)));
|
||||
v_store_aligned(sum_g + j, v_muladd(kg, w, vx_load_aligned(sum_g + j)));
|
||||
v_store_aligned(sum_r + j, v_muladd(kr, w, vx_load_aligned(sum_r + j)));
|
||||
v_store_aligned(sum_b + j, v_muladd(kb & knan, w, vx_load_aligned(sum_b + j)));
|
||||
v_store_aligned(sum_g + j, v_muladd(kg & knan, w, vx_load_aligned(sum_g + j)));
|
||||
v_store_aligned(sum_r + j, v_muladd(kr & knan, w, vx_load_aligned(sum_r + j)));
|
||||
}
|
||||
#endif
|
||||
for (; j < size.width; j++, ksptr += 3, rsptr += 3)
|
||||
{
|
||||
float b = ksptr[0], g = ksptr[1], r = ksptr[2];
|
||||
float alpha = (std::abs(b - rsptr[0]) + std::abs(g - rsptr[1]) + std::abs(r - rsptr[2])) * scale_index;
|
||||
bool v_NAN = cvIsNaN(b) || cvIsNaN(g) || cvIsNaN(r);
|
||||
float rb = rsptr[0], rg = rsptr[1], rr = rsptr[2];
|
||||
bool r_NAN = cvIsNaN(rb) || cvIsNaN(rg) || cvIsNaN(rr);
|
||||
float alpha = (std::abs(b - rb) + std::abs(g - rg) + std::abs(r - rr)) * scale_index;
|
||||
int idx = cvFloor(alpha);
|
||||
alpha -= idx;
|
||||
float w = space_weight[k] * (expLUT[idx] + alpha*(expLUT[idx + 1] - expLUT[idx]));
|
||||
wsum[j] += w;
|
||||
sum_b[j] += b*w;
|
||||
sum_g[j] += g*w;
|
||||
sum_r[j] += r*w;
|
||||
if (!v_NAN)
|
||||
{
|
||||
float w = space_weight[k] * (r_NAN ? 1.f : (expLUT[idx] + alpha*(expLUT[idx + 1] - expLUT[idx])));
|
||||
wsum[j] += w;
|
||||
sum_b[j] += b*w;
|
||||
sum_g[j] += g*w;
|
||||
sum_r[j] += r*w;
|
||||
}
|
||||
}
|
||||
}
|
||||
j = 0;
|
||||
#if CV_SIMD
|
||||
for (; j <= size.width - v_float32::nlanes; j += v_float32::nlanes, dptr += 3*v_float32::nlanes)
|
||||
for (; j <= size.width - v_float32::nlanes; j += v_float32::nlanes, sptr += 3*v_float32::nlanes, dptr += 3*v_float32::nlanes)
|
||||
{
|
||||
v_float32 w = v_one / vx_load_aligned(wsum + j);
|
||||
v_store_interleave(dptr, vx_load_aligned(sum_b + j) * w, vx_load_aligned(sum_g + j) * w, vx_load_aligned(sum_r + j) * w);
|
||||
v_float32 b, g, r;
|
||||
v_load_deinterleave(sptr, b, g, r);
|
||||
v_float32 mask = v_not_nan(b) & v_not_nan(g) & v_not_nan(r);
|
||||
v_float32 w = v_one / (vx_load_aligned(wsum + j) + (v_one & mask));
|
||||
v_store_interleave(dptr, (vx_load_aligned(sum_b + j) + (b & mask)) * w, (vx_load_aligned(sum_g + j) + (g & mask)) * w, (vx_load_aligned(sum_r + j) + (r & mask)) * w);
|
||||
}
|
||||
#endif
|
||||
for (; j < size.width; j++)
|
||||
{
|
||||
CV_DbgAssert(fabs(wsum[j]) > 0);
|
||||
wsum[j] = 1.f / wsum[j];
|
||||
*(dptr++) = sum_b[j] * wsum[j];
|
||||
*(dptr++) = sum_g[j] * wsum[j];
|
||||
*(dptr++) = sum_r[j] * wsum[j];
|
||||
CV_DbgAssert(fabs(wsum[j]) >= 0);
|
||||
float b = *(sptr++);
|
||||
float g = *(sptr++);
|
||||
float r = *(sptr++);
|
||||
if (cvIsNaN(b) || cvIsNaN(g) || cvIsNaN(r))
|
||||
{
|
||||
wsum[j] = 1.f / wsum[j];
|
||||
*(dptr++) = sum_b[j] * wsum[j];
|
||||
*(dptr++) = sum_g[j] * wsum[j];
|
||||
*(dptr++) = sum_r[j] * wsum[j];
|
||||
}
|
||||
else
|
||||
{
|
||||
wsum[j] = 1.f / (wsum[j] + 1.f);
|
||||
*(dptr++) = (sum_b[j] + b) * wsum[j];
|
||||
*(dptr++) = (sum_g[j] + g) * wsum[j];
|
||||
*(dptr++) = (sum_r[j] + r) * wsum[j];
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -585,9 +1196,7 @@ bilateralFilter_32f( const Mat& src, Mat& dst, int d,
|
||||
// temporary copy of the image with borders for easy processing
|
||||
Mat temp;
|
||||
copyMakeBorder( src, temp, radius, radius, radius, radius, borderType );
|
||||
minValSrc -= 5. * sigma_color;
|
||||
patchNaNs( temp, minValSrc ); // this replacement of NaNs makes the assumption that depth values are nonnegative
|
||||
// TODO: make replacement parameter avalible in the outside function interface
|
||||
|
||||
// allocate lookup tables
|
||||
std::vector<float> _space_weight(d*d);
|
||||
std::vector<int> _space_ofs(d*d);
|
||||
@ -620,7 +1229,7 @@ bilateralFilter_32f( const Mat& src, Mat& dst, int d,
|
||||
for( j = -radius; j <= radius; j++ )
|
||||
{
|
||||
double r = std::sqrt((double)i*i + (double)j*j);
|
||||
if( r > radius )
|
||||
if( r > radius || ( i == 0 && j == 0 ) )
|
||||
continue;
|
||||
space_weight[maxk] = (float)std::exp(r*r*gauss_space_coeff);
|
||||
space_ofs[maxk++] = (int)(i*(temp.step/sizeof(float)) + j*cn);
|
||||
|
||||
Loading…
Reference in New Issue
Block a user