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378 lines
14 KiB
ReStructuredText
HDR imaging
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=============
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.. highlight:: cpp
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This section describes high dynamic range imaging algorithms namely tonemapping, exposure alignment, camera calibration with multiple exposures and exposure fusion.
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Tonemap
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---------------------------
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.. ocv:class:: Tonemap : public Algorithm
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Base class for tonemapping algorithms - tools that are used to map HDR image to 8-bit range.
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Tonemap::process
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---------------------------
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Tonemaps image
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.. ocv:function:: void Tonemap::process(InputArray src, OutputArray dst)
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:param src: source image - 32-bit 3-channel Mat
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:param dst: destination image - 32-bit 3-channel Mat with values in [0, 1] range
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createTonemap
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---------------------------
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Creates simple linear mapper with gamma correction
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.. ocv:function:: Ptr<Tonemap> createTonemap(float gamma = 1.0f)
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:param gamma: positive value for gamma correction. Gamma value of 1.0 implies no correction, gamma equal to 2.2f is suitable for most displays.
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Generally gamma > 1 brightens the image and gamma < 1 darkens it.
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TonemapDrago
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---------------------------
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.. ocv:class:: TonemapDrago : public Tonemap
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Adaptive logarithmic mapping is a fast global tonemapping algorithm that scales the image in logarithmic domain.
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Since it's a global operator the same function is applied to all the pixels, it is controlled by the bias parameter.
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Optional saturation enhancement is possible as described in [FL02]_.
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For more information see [DM03]_.
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createTonemapDrago
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---------------------------
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Creates TonemapDrago object
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.. ocv:function:: Ptr<TonemapDrago> createTonemapDrago(float gamma = 1.0f, float saturation = 1.0f, float bias = 0.85f)
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:param gamma: gamma value for gamma correction. See :ocv:func:`createTonemap`
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:param saturation: positive saturation enhancement value. 1.0 preserves saturation, values greater than 1 increase saturation and values less than 1 decrease it.
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:param bias: value for bias function in [0, 1] range. Values from 0.7 to 0.9 usually give best results, default value is 0.85.
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TonemapDurand
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---------------------------
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.. ocv:class:: TonemapDurand : public Tonemap
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This algorithm decomposes image into two layers: base layer and detail layer using bilateral filter and compresses contrast of the base layer thus preserving all the details.
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This implementation uses regular bilateral filter from opencv.
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Saturation enhancement is possible as in ocv:class:`TonemapDrago`.
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For more information see [DD02]_.
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createTonemapDurand
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---------------------------
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Creates TonemapDurand object
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.. ocv:function:: Ptr<TonemapDurand> createTonemapDurand(float gamma = 1.0f, float contrast = 4.0f, float saturation = 1.0f, float sigma_space = 2.0f, float sigma_color = 2.0f)
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:param gamma: gamma value for gamma correction. See :ocv:func:`createTonemap`
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:param contrast: resulting contrast on logarithmic scale, i. e. log(max / min), where max and min are maximum and minimum luminance values of the resulting image.
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:param saturation: saturation enhancement value. See :ocv:func:`createTonemapDrago`
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:param sigma_space: bilateral filter sigma in color space
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:param sigma_color: bilateral filter sigma in coordinate space
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TonemapReinhard
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---------------------------
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.. ocv:class:: TonemapReinhard : public Tonemap
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This is a global tonemapping operator that models human visual system.
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Mapping function is controlled by adaptation parameter, that is computed using light adaptation and color adaptation.
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For more information see [RD05]_.
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createTonemapReinhard
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---------------------------
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Creates TonemapReinhard object
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.. ocv:function:: Ptr<TonemapReinhard> createTonemapReinhard(float gamma = 1.0f, float intensity = 0.0f, float light_adapt = 1.0f, float color_adapt = 0.0f)
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:param gamma: gamma value for gamma correction. See :ocv:func:`createTonemap`
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:param intensity: result intensity in [-8, 8] range. Greater intensity produces brighter results.
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:param light_adapt: light adaptation in [0, 1] range. If 1 adaptation is based only on pixel value, if 0 it's global, otherwise it's a weighted mean of this two cases.
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:param color_adapt: chromatic adaptation in [0, 1] range. If 1 channels are treated independently, if 0 adaptation level is the same for each channel.
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TonemapMantiuk
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---------------------------
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.. ocv:class:: TonemapMantiuk : public Tonemap
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This algorithm transforms image to contrast using gradients on all levels of gaussian pyramid, transforms contrast values to HVS response and scales the response.
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After this the image is reconstructed from new contrast values.
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For more information see [MM06]_.
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createTonemapMantiuk
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---------------------------
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Creates TonemapMantiuk object
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.. ocv:function:: Ptr<TonemapMantiuk> createTonemapMantiuk(float gamma = 1.0f, float scale = 0.7f, float saturation = 1.0f)
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:param gamma: gamma value for gamma correction. See :ocv:func:`createTonemap`
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:param scale: contrast scale factor. HVS response is multiplied by this parameter, thus compressing dynamic range. Values from 0.6 to 0.9 produce best results.
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:param saturation: saturation enhancement value. See :ocv:func:`createTonemapDrago`
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AlignExposures
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---------------------------
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.. ocv:class:: AlignExposures : public Algorithm
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The base class for algorithms that align images of the same scene with different exposures
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AlignExposures::process
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---------------------------
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Aligns images
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.. ocv:function:: void AlignExposures::process(InputArrayOfArrays src, std::vector<Mat>& dst, InputArray times, InputArray response)
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:param src: vector of input images
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:param dst: vector of aligned images
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:param times: vector of exposure time values for each image
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:param response: 256x1 matrix with inverse camera response function for each pixel value, it should have the same number of channels as images.
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AlignMTB
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---------------------------
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.. ocv:class:: AlignMTB : public AlignExposures
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This algorithm converts images to median threshold bitmaps (1 for pixels brighter than median luminance and 0 otherwise) and than aligns the resulting bitmaps using bit operations.
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It is invariant to exposure, so exposure values and camera response are not necessary.
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In this implementation new image regions are filled with zeros.
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For more information see [GW03]_.
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AlignMTB::process
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---------------------------
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Short version of process, that doesn't take extra arguments.
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.. ocv:function:: void AlignMTB::process(InputArrayOfArrays src, std::vector<Mat>& dst)
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:param src: vector of input images
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:param dst: vector of aligned images
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AlignMTB::calculateShift
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---------------------------
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Calculates shift between two images, i. e. how to shift the second image to correspond it with the first.
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.. ocv:function:: Point AlignMTB::calculateShift(InputArray img0, InputArray img1)
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:param img0: first image
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:param img1: second image
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AlignMTB::shiftMat
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---------------------------
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Helper function, that shift Mat filling new regions with zeros.
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.. ocv:function:: void AlignMTB::shiftMat(InputArray src, OutputArray dst, const Point shift)
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:param src: input image
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:param dst: result image
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:param shift: shift value
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AlignMTB::computeBitmaps
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---------------------------
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Computes median threshold and exclude bitmaps of given image.
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.. ocv:function:: void AlignMTB::computeBitmaps(InputArray img, OutputArray tb, OutputArray eb)
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:param img: input image
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:param tb: median threshold bitmap
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:param eb: exclude bitmap
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createAlignMTB
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---------------------------
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Creates AlignMTB object
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.. ocv:function:: Ptr<AlignMTB> createAlignMTB(int max_bits = 6, int exclude_range = 4, bool cut = true)
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:param max_bits: logarithm to the base 2 of maximal shift in each dimension. Values of 5 and 6 are usually good enough (31 and 63 pixels shift respectively).
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:param exclude_range: range for exclusion bitmap that is constructed to suppress noise around the median value.
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:param cut: if true cuts images, otherwise fills the new regions with zeros.
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CalibrateCRF
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---------------------------
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.. ocv:class:: CalibrateCRF : public Algorithm
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The base class for camera response calibration algorithms.
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CalibrateCRF::process
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---------------------------
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Recovers inverse camera response.
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.. ocv:function:: void CalibrateCRF::process(InputArrayOfArrays src, OutputArray dst, InputArray times)
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:param src: vector of input images
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:param dst: 256x1 matrix with inverse camera response function
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:param times: vector of exposure time values for each image
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CalibrateDebevec
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---------------------------
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.. ocv:class:: CalibrateDebevec : public CalibrateCRF
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Inverse camera response function is extracted for each brightness value by minimizing an objective function as linear system.
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Objective function is constructed using pixel values on the same position in all images, extra term is added to make the result smoother.
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For more information see [DM97]_.
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createCalibrateDebevec
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---------------------------
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Creates CalibrateDebevec object
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.. ocv:function:: createCalibrateDebevec(int samples = 70, float lambda = 10.0f, bool random = false)
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:param samples: number of pixel locations to use
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:param lambda: smoothness term weight. Greater values produce smoother results, but can alter the response.
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:param random: if true sample pixel locations are chosen at random, otherwise the form a rectangular grid.
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CalibrateRobertson
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---------------------------
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.. ocv:class:: CalibrateRobertson : public CalibrateCRF
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Inverse camera response function is extracted for each brightness value by minimizing an objective function as linear system.
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This algorithm uses all image pixels.
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For more information see [RB99]_.
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createCalibrateRobertson
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---------------------------
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Creates CalibrateRobertson object
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.. ocv:function:: createCalibrateRobertson(int max_iter = 30, float threshold = 0.01f)
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:param max_iter: maximal number of Gauss-Seidel solver iterations.
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:param threshold: target difference between results of two successive steps of the minimization.
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MergeExposures
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---------------------------
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.. ocv:class:: MergeExposures : public Algorithm
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The base class algorithms that can merge exposure sequence to a single image.
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MergeExposures::process
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---------------------------
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Merges images.
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.. ocv:function:: void MergeExposures::process(InputArrayOfArrays src, OutputArray dst, InputArray times, InputArray response)
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:param src: vector of input images
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:param dst: result image
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:param times: vector of exposure time values for each image
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:param response: 256x1 matrix with inverse camera response function for each pixel value, it should have the same number of channels as images.
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MergeDebevec
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---------------------------
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.. ocv:class:: MergeDebevec : public MergeExposures
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The resulting HDR image is calculated as weighted average of the exposures considering exposure values and camera response.
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For more information see [DM97]_.
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createMergeDebevec
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---------------------------
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Creates MergeDebevec object
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.. ocv:function:: Ptr<MergeDebevec> createMergeDebevec()
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MergeMertens
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---------------------------
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.. ocv:class:: MergeMertens : public MergeExposures
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Pixels are weighted using contrast, saturation and well-exposedness measures, than images are combined using laplacian pyramids.
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The resulting image weight is constructed as weighted average of contrast, saturation and well-exposedness measures.
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The resulting image doesn't require tonemapping and can be converted to 8-bit image by multiplying by 255, but it's recommended to apply gamma correction and/or linear tonemapping.
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For more information see [MK07]_.
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MergeMertens::process
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---------------------------
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Short version of process, that doesn't take extra arguments.
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.. ocv:function:: void MergeMertens::process(InputArrayOfArrays src, OutputArray dst)
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:param src: vector of input images
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:param dst: result image
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createMergeMertens
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---------------------------
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Creates MergeMertens object
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.. ocv:function:: Ptr<MergeMertens> createMergeMertens(float contrast_weight = 1.0f, float saturation_weight = 1.0f, float exposure_weight = 0.0f)
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:param contrast_weight: contrast measure weight. See :ocv:class:`MergeMertens`.
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:param saturation_weight: saturation measure weight
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:param exposure_weight: well-exposedness measure weight
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MergeRobertson
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---------------------------
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.. ocv:class:: MergeRobertson : public MergeExposures
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The resulting HDR image is calculated as weighted average of the exposures considering exposure values and camera response.
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For more information see [RB99]_.
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createMergeRobertson
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---------------------------
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Creates MergeRobertson object
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.. ocv:function:: Ptr<MergeRobertson> createMergeRobertson()
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References
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.. [DM03] F. Drago, K. Myszkowski, T. Annen, N. Chiba, "Adaptive Logarithmic Mapping For Displaying High Contrast Scenes", Computer Graphics Forum, 2003, 22, 419 - 426.
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.. [FL02] R. Fattal, D. Lischinski, M. Werman, "Gradient Domain High Dynamic Range Compression", Proceedings OF ACM SIGGRAPH, 2002, 249 - 256.
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.. [DD02] F. Durand and Julie Dorsey, "Fast Bilateral Filtering for the Display of High-Dynamic-Range Images", ACM Transactions on Graphics, 2002, 21, 3, 257 - 266.
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.. [RD05] E. Reinhard, K. Devlin, "Dynamic Range Reduction Inspired by Photoreceptor Physiology", IEEE Transactions on Visualization and Computer Graphics, 2005, 11, 13 - 24.
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.. [MM06] R. Mantiuk, K. Myszkowski, H.-P. Seidel, "Perceptual Framework for Contrast Processing of High Dynamic Range Images", ACM Transactions on Applied Perception, 2006, 3, 3, 286 - 308.
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.. [GW03] G. Ward, "Fast, Robust Image Registration for Compositing High Dynamic Range Photographs from Handheld Exposures", Journal of Graphics Tools, 2003, 8, 17 - 30.
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.. [DM97] P. Debevec, J. Malik, "Recovering High Dynamic Range Radiance Maps from Photographs", Proceedings OF ACM SIGGRAPH, 1997, 369 - 378.
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.. [MK07] T. Mertens, J. Kautz, F. Van Reeth, "Exposure Fusion", Proceedings of the 15th Pacific Conference on Computer Graphics and Applications, 2007, 382 - 390.
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.. [RB99] M. Robertson , S. Borman , R. Stevenson , "Dynamic range improvement through multiple exposures ", Proceedings of the Int. Conf. on Image Processing , 1999, 159 - 163.
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