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Merge pull request #27097 from amane-ame:blur_hal_rvv

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Add RISC-V HAL implementation for cv::blur series #27097

This patch implements `cv_hal_gaussianBlurBinomial`, `cv_hal_medianBlur`, `cv_hal_boxFilter` and `cv_hal_bilateralFilter` using native intrinsics, optimizing the performance of `cv::GaussianBlur/cv::medianBlur/cv::boxFilter/cv::bilateralFilter` for `3x3/5x5` kernels.

Tested on MUSE-PI (Spacemit X60) for both gcc 14.2 and clang 20.0.

```
$ ./opencv_test_imgproc --gtest_filter="*Filter*:*Blur*"
$ ./opencv_perf_imgproc --gtest_filter="*gauss*:*box*:*Bilateral*:*median*" --perf_min_samples=2000 --perf_force_samples=2000
```

View the full perf table here: [hal_rvv_blur.pdf](https://github.com/user-attachments/files/19335582/hal_rvv_blur.pdf)

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [ ] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
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天音あめ 2025-03-20 17:59:59 +08:00 committed by GitHub
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1827
3rdparty/hal_rvv/hal_rvv_1p0/filter.hpp vendored
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7
3rdparty/hal_rvv/hal_rvv_1p0/types.hpp vendored
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@ -209,6 +209,13 @@ static inline VecType vmul(VecType vs2, VecType vs1, size_t vl) {
return __riscv_v##IS_F##mul(vs2, vs1, vl); \ return __riscv_v##IS_F##mul(vs2, vs1, vl); \
} \ } \
\ \
static inline VecType vslide1down(VecType vs2, ElemType vs1, size_t vl) { \
return __riscv_v##IS_F##slide1down(vs2, vs1, vl); \
} \
static inline VecType vslide1up(VecType vs2, ElemType vs1, size_t vl) { \
return __riscv_v##IS_F##slide1up(vs2, vs1, vl); \
} \
\
static inline VecType vmin(VecType vs2, VecType vs1, size_t vl) { \ static inline VecType vmin(VecType vs2, VecType vs1, size_t vl) { \
return __riscv_v##IS_F##min##IS_U(vs2, vs1, vl); \ return __riscv_v##IS_F##min##IS_U(vs2, vs1, vl); \
} \ } \