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Addition of per-channel h-values for fastNlMeansDenoising[Multi][Abs]
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@@ -138,6 +138,31 @@ parameter.
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CV_EXPORTS_W void fastNlMeansDenoising( InputArray src, OutputArray dst, float h = 3,
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int templateWindowSize = 7, int searchWindowSize = 21);
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/** @brief Perform image denoising using Non-local Means Denoising algorithm
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<http://www.ipol.im/pub/algo/bcm_non_local_means_denoising/> with several computational
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optimizations. Noise expected to be a gaussian white noise
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@param src Input 8-bit 1-channel, 2-channel, 3-channel or 4-channel image.
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@param dst Output image with the same size and type as src .
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@param templateWindowSize Size in pixels of the template patch that is used to compute weights.
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Should be odd. Recommended value 7 pixels
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@param searchWindowSize Size in pixels of the window that is used to compute weighted average for
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given pixel. Should be odd. Affect performance linearly: greater searchWindowsSize - greater
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denoising time. Recommended value 21 pixels
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@param h Array of parameters regulating filter strength, one per
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channel. Big h value perfectly removes noise but also removes image
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details, smaller h value preserves details but also preserves some
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noise
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This function expected to be applied to grayscale images. For colored images look at
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fastNlMeansDenoisingColored. Advanced usage of this functions can be manual denoising of colored
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image in different colorspaces. Such approach is used in fastNlMeansDenoisingColored by converting
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image to CIELAB colorspace and then separately denoise L and AB components with different h
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parameter.
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*/
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CV_EXPORTS_W void fastNlMeansDenoising( InputArray src, OutputArray dst, float *h,
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int templateWindowSize = 7, int searchWindowSize = 21);
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/** @brief Perform image denoising using Non-local Means Denoising
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algorithm <http://www.ipol.im/pub/algo/bcm_non_local_means_denoising/>
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with several computational optimizations. Noise expected to be a
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@@ -163,6 +188,33 @@ parameter.
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CV_EXPORTS_W void fastNlMeansDenoisingAbs( InputArray src, OutputArray dst, float h = 3,
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int templateWindowSize = 7, int searchWindowSize = 21);
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/** @brief Perform image denoising using Non-local Means Denoising
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algorithm <http://www.ipol.im/pub/algo/bcm_non_local_means_denoising/>
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with several computational optimizations. Noise expected to be a
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gaussian white noise. Uses squared sum of absolute value distances
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instead of sum of squared distances for weight calculation
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@param src Input 8-bit or 16-bit 1-channel, 2-channel, 3-channel or 4-channel image.
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@param dst Output image with the same size and type as src .
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@param templateWindowSize Size in pixels of the template patch that is used to compute weights.
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Should be odd. Recommended value 7 pixels
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@param searchWindowSize Size in pixels of the window that is used to compute weighted average for
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given pixel. Should be odd. Affect performance linearly: greater searchWindowsSize - greater
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denoising time. Recommended value 21 pixels
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@param h Array of parameters regulating filter strength, one per
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channel. Big h value perfectly removes noise but also removes image
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details, smaller h value preserves details but also preserves some
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noise
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This function expected to be applied to grayscale images. For colored images look at
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fastNlMeansDenoisingColored. Advanced usage of this functions can be manual denoising of colored
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image in different colorspaces. Such approach is used in fastNlMeansDenoisingColored by converting
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image to CIELAB colorspace and then separately denoise L and AB components with different h
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parameter.
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*/
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CV_EXPORTS_W void fastNlMeansDenoisingAbs( InputArray src, OutputArray dst, float *h,
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int templateWindowSize = 7, int searchWindowSize = 21);
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/** @brief Modification of fastNlMeansDenoising function for colored images
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@param src Input 8-bit 3-channel image.
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@@ -204,14 +256,73 @@ Should be odd. Recommended value 7 pixels
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@param searchWindowSize Size in pixels of the window that is used to compute weighted average for
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given pixel. Should be odd. Affect performance linearly: greater searchWindowsSize - greater
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denoising time. Recommended value 21 pixels
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@param h Parameter regulating filter strength for luminance component. Bigger h value perfectly
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removes noise but also removes image details, smaller h value preserves details but also preserves
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some noise
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@param h Parameter regulating filter strength. Bigger h value
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perfectly removes noise but also removes image details, smaller h
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value preserves details but also preserves some noise
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*/
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CV_EXPORTS_W void fastNlMeansDenoisingMulti( InputArrayOfArrays srcImgs, OutputArray dst,
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int imgToDenoiseIndex, int temporalWindowSize,
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float h = 3, int templateWindowSize = 7, int searchWindowSize = 21);
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/** @brief Modification of fastNlMeansDenoising function for images sequence where consequtive images have been
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captured in small period of time. For example video. This version of the function is for grayscale
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images or for manual manipulation with colorspaces. For more details see
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<http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.131.6394>
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@param srcImgs Input 8-bit 1-channel, 2-channel, 3-channel or
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4-channel images sequence. All images should have the same type and
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size.
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@param imgToDenoiseIndex Target image to denoise index in srcImgs sequence
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@param temporalWindowSize Number of surrounding images to use for target image denoising. Should
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be odd. Images from imgToDenoiseIndex - temporalWindowSize / 2 to
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imgToDenoiseIndex - temporalWindowSize / 2 from srcImgs will be used to denoise
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srcImgs[imgToDenoiseIndex] image.
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@param dst Output image with the same size and type as srcImgs images.
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@param templateWindowSize Size in pixels of the template patch that is used to compute weights.
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Should be odd. Recommended value 7 pixels
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@param searchWindowSize Size in pixels of the window that is used to compute weighted average for
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given pixel. Should be odd. Affect performance linearly: greater searchWindowsSize - greater
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denoising time. Recommended value 21 pixels
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@param h Array of parameters regulating filter strength, one for each
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channel. Bigger h value perfectly removes noise but also removes image
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details, smaller h value preserves details but also preserves some
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noise
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*/
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CV_EXPORTS_W void fastNlMeansDenoisingMulti( InputArrayOfArrays srcImgs, OutputArray dst,
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int imgToDenoiseIndex, int temporalWindowSize,
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float *h , int templateWindowSize = 7, int searchWindowSize = 21);
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/** @brief Modification of fastNlMeansDenoising function for images
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sequence where consequtive images have been captured in small period
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of time. For example video. This version of the function is for
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grayscale images or for manual manipulation with colorspaces. For more
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details see
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<http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.131.6394>. Uses
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squared sum of absolute value distances instead of sum of squared
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distances for weight calculation
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@param srcImgs Input 8-bit or 16-bit 1-channel, 2-channel, 3-channel
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or 4-channel images sequence. All images should have the same type and
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size.
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@param imgToDenoiseIndex Target image to denoise index in srcImgs sequence
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@param temporalWindowSize Number of surrounding images to use for target image denoising. Should
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be odd. Images from imgToDenoiseIndex - temporalWindowSize / 2 to
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imgToDenoiseIndex - temporalWindowSize / 2 from srcImgs will be used to denoise
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srcImgs[imgToDenoiseIndex] image.
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@param dst Output image with the same size and type as srcImgs images.
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@param templateWindowSize Size in pixels of the template patch that is used to compute weights.
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Should be odd. Recommended value 7 pixels
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@param searchWindowSize Size in pixels of the window that is used to compute weighted average for
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given pixel. Should be odd. Affect performance linearly: greater searchWindowsSize - greater
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denoising time. Recommended value 21 pixels
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@param h Parameter regulating filter strength. Bigger h value
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perfectly removes noise but also removes image details, smaller h
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value preserves details but also preserves some noise
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*/
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CV_EXPORTS_W void fastNlMeansDenoisingMultiAbs( InputArrayOfArrays srcImgs, OutputArray dst,
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int imgToDenoiseIndex, int temporalWindowSize,
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float h = 3, int templateWindowSize = 7, int searchWindowSize = 21);
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/** @brief Modification of fastNlMeansDenoising function for images
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sequence where consequtive images have been captured in small period
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of time. For example video. This version of the function is for
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@@ -235,13 +346,14 @@ Should be odd. Recommended value 7 pixels
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@param searchWindowSize Size in pixels of the window that is used to compute weighted average for
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given pixel. Should be odd. Affect performance linearly: greater searchWindowsSize - greater
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denoising time. Recommended value 21 pixels
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@param h Parameter regulating filter strength for luminance component. Bigger h value perfectly
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removes noise but also removes image details, smaller h value preserves details but also preserves
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some noise
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@param h Array of parameters regulating filter strength, one for each
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channel. Bigger h value perfectly removes noise but also removes image
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details, smaller h value preserves details but also preserves some
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noise
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*/
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CV_EXPORTS_W void fastNlMeansDenoisingMultiAbs( InputArrayOfArrays srcImgs, OutputArray dst,
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int imgToDenoiseIndex, int temporalWindowSize,
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float h = 3, int templateWindowSize = 7, int searchWindowSize = 21);
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float *h, int templateWindowSize = 7, int searchWindowSize = 21);
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/** @brief Modification of fastNlMeansDenoisingMulti function for colored images sequences
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