187 lines
8.9 KiB
C++
187 lines
8.9 KiB
C++
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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#ifndef __OPENCV_BM3D_IMAGE_DENOISING_HPP__
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#define __OPENCV_BM3D_IMAGE_DENOISING_HPP__
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/** @file
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@date Jul 19, 2016
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@author Bartek Pawlik
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*/
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#include <opencv2/core.hpp>
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namespace cv
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{
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namespace xphoto
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{
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//! @addtogroup xphoto
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//! @{
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//! BM3D transform types
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enum TransformTypes
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{
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/** Un-normalized Haar transform */
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HAAR = 0
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};
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//! BM3D algorithm steps
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enum Bm3dSteps
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{
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/** Execute all steps of the algorithm */
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BM3D_STEPALL = 0,
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/** Execute only first step of the algorithm */
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BM3D_STEP1 = 1,
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/** Execute only second step of the algorithm */
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BM3D_STEP2 = 2
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};
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/** @brief Performs image denoising using the Block-Matching and 3D-filtering algorithm
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<http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf> 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 or 16-bit 1-channel image.
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@param dstStep1 Output image of the first step of BM3D with the same size and type as src.
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@param dstStep2 Output image of the second step of BM3D with the same size and type as src.
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@param h Parameter regulating filter strength. Big h value perfectly removes noise but also
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removes image details, smaller h value preserves details but also preserves some noise.
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@param templateWindowSize Size in pixels of the template patch that is used for block-matching.
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Should be power of 2.
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@param searchWindowSize Size in pixels of the window that is used to perform block-matching.
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Affect performance linearly: greater searchWindowsSize - greater denoising time.
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Must be larger than templateWindowSize.
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@param blockMatchingStep1 Block matching threshold for the first step of BM3D (hard thresholding),
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i.e. maximum distance for which two blocks are considered similar.
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Value expressed in euclidean distance.
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@param blockMatchingStep2 Block matching threshold for the second step of BM3D (Wiener filtering),
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i.e. maximum distance for which two blocks are considered similar.
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Value expressed in euclidean distance.
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@param groupSize Maximum size of the 3D group for collaborative filtering.
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@param slidingStep Sliding step to process every next reference block.
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@param beta Kaiser window parameter that affects the sidelobe attenuation of the transform of the
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window. Kaiser window is used in order to reduce border effects. To prevent usage of the window,
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set beta to zero.
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@param normType Norm used to calculate distance between blocks. L2 is slower than L1
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but yields more accurate results.
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@param step Step of BM3D to be executed. Possible variants are: step 1, step 2, both steps.
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@param transformType Type of the orthogonal transform used in collaborative filtering step.
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Currently only Haar transform is supported.
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This function expected to be applied to grayscale images. Advanced usage of this function
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can be manual denoising of colored image in different colorspaces.
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@sa
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fastNlMeansDenoising
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*/
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CV_EXPORTS_W void bm3dDenoising(
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InputArray src,
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InputOutputArray dstStep1,
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OutputArray dstStep2,
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float h = 1,
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int templateWindowSize = 4,
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int searchWindowSize = 16,
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int blockMatchingStep1 = 2500,
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int blockMatchingStep2 = 400,
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int groupSize = 8,
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int slidingStep = 1,
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float beta = 2.0f,
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int normType = cv::NORM_L2,
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int step = cv::xphoto::BM3D_STEPALL,
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int transformType = cv::xphoto::HAAR);
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/** @brief Performs image denoising using the Block-Matching and 3D-filtering algorithm
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<http://www.cs.tut.fi/~foi/GCF-BM3D/BM3D_TIP_2007.pdf> 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 or 16-bit 1-channel image.
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@param dst Output image with the same size and type as src.
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@param h Parameter regulating filter strength. Big h value perfectly removes noise but also
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removes image details, smaller h value preserves details but also preserves some noise.
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@param templateWindowSize Size in pixels of the template patch that is used for block-matching.
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Should be power of 2.
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@param searchWindowSize Size in pixels of the window that is used to perform block-matching.
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Affect performance linearly: greater searchWindowsSize - greater denoising time.
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Must be larger than templateWindowSize.
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@param blockMatchingStep1 Block matching threshold for the first step of BM3D (hard thresholding),
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i.e. maximum distance for which two blocks are considered similar.
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Value expressed in euclidean distance.
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@param blockMatchingStep2 Block matching threshold for the second step of BM3D (Wiener filtering),
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i.e. maximum distance for which two blocks are considered similar.
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Value expressed in euclidean distance.
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@param groupSize Maximum size of the 3D group for collaborative filtering.
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@param slidingStep Sliding step to process every next reference block.
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@param beta Kaiser window parameter that affects the sidelobe attenuation of the transform of the
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window. Kaiser window is used in order to reduce border effects. To prevent usage of the window,
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set beta to zero.
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@param normType Norm used to calculate distance between blocks. L2 is slower than L1
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but yields more accurate results.
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@param step Step of BM3D to be executed. Allowed are only BM3D_STEP1 and BM3D_STEPALL.
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BM3D_STEP2 is not allowed as it requires basic estimate to be present.
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@param transformType Type of the orthogonal transform used in collaborative filtering step.
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Currently only Haar transform is supported.
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This function expected to be applied to grayscale images. Advanced usage of this function
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can be manual denoising of colored image in different colorspaces.
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@sa
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fastNlMeansDenoising
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*/
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CV_EXPORTS_W void bm3dDenoising(
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InputArray src,
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OutputArray dst,
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float h = 1,
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int templateWindowSize = 4,
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int searchWindowSize = 16,
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int blockMatchingStep1 = 2500,
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int blockMatchingStep2 = 400,
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int groupSize = 8,
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int slidingStep = 1,
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float beta = 2.0f,
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int normType = cv::NORM_L2,
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int step = cv::xphoto::BM3D_STEPALL,
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int transformType = cv::xphoto::HAAR);
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//! @}
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}
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}
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#endif // __OPENCV_BM3D_IMAGE_DENOISING_HPP__
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