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157 lines
7.5 KiB
157 lines
7.5 KiB
/*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) 2008-2012, 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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// * 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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// * 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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// 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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// loss of use, data, or profits; or business interruption) however caused |
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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_PHOTO_CUDA_HPP |
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#define OPENCV_PHOTO_CUDA_HPP |
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#include "opencv2/core/cuda.hpp" |
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namespace cv { namespace cuda { |
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//! @addtogroup photo_denoise |
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//! @{ |
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/** @brief Performs pure non local means denoising without any simplification, and thus it is not fast. |
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@param src Source image. Supports only CV_8UC1, CV_8UC2 and CV_8UC3. |
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@param dst Destination image. |
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@param h Filter sigma regulating filter strength for color. |
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@param search_window Size of search window. |
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@param block_size Size of block used for computing weights. |
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@param borderMode Border type. See borderInterpolate for details. BORDER_REFLECT101 , |
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BORDER_REPLICATE , BORDER_CONSTANT , BORDER_REFLECT and BORDER_WRAP are supported for now. |
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@param stream Stream for the asynchronous version. |
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@sa |
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fastNlMeansDenoising |
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*/ |
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CV_EXPORTS void nonLocalMeans(InputArray src, OutputArray dst, |
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float h, |
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int search_window = 21, |
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int block_size = 7, |
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int borderMode = BORDER_DEFAULT, |
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Stream& stream = Stream::Null()); |
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CV_WRAP inline void nonLocalMeans(const GpuMat& src, CV_OUT GpuMat& dst, |
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float h, |
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int search_window = 21, |
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int block_size = 7, |
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int borderMode = BORDER_DEFAULT, |
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Stream& stream = Stream::Null()) |
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{ |
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nonLocalMeans(InputArray(src), OutputArray(dst), h, search_window, block_size, borderMode, stream); |
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}; |
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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 or 3-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 search_window 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 search_window - greater |
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denoising time. Recommended value 21 pixels |
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@param block_size Size in pixels of the template patch that is used to compute weights. Should be |
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odd. Recommended value 7 pixels |
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@param stream Stream for the asynchronous invocations. |
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This function expected to be applied to grayscale images. For colored images look at |
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FastNonLocalMeansDenoising::labMethod. |
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@sa |
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fastNlMeansDenoising |
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*/ |
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CV_EXPORTS void fastNlMeansDenoising(InputArray src, OutputArray dst, |
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float h, |
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int search_window = 21, |
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int block_size = 7, |
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Stream& stream = Stream::Null()); |
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CV_WRAP inline void fastNlMeansDenoising(const GpuMat& src, CV_OUT GpuMat& dst, |
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float h, |
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int search_window = 21, |
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int block_size = 7, |
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Stream& stream = Stream::Null()) |
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{ |
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fastNlMeansDenoising(InputArray(src), OutputArray(dst), h, search_window, block_size, stream); |
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} |
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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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@param dst Output image with the same size and type as src . |
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@param h_luminance Parameter regulating filter strength. Big h value perfectly removes noise but |
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also removes image details, smaller h value preserves details but also preserves some noise |
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@param photo_render float The same as h but for color components. For most images value equals 10 will be |
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enough to remove colored noise and do not distort colors |
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@param search_window 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 search_window - greater |
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denoising time. Recommended value 21 pixels |
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@param block_size Size in pixels of the template patch that is used to compute weights. Should be |
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odd. Recommended value 7 pixels |
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@param stream Stream for the asynchronous invocations. |
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The function converts image to CIELAB colorspace and then separately denoise L and AB components |
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with given h parameters using FastNonLocalMeansDenoising::simpleMethod function. |
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@sa |
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fastNlMeansDenoisingColored |
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*/ |
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CV_EXPORTS void fastNlMeansDenoisingColored(InputArray src, OutputArray dst, |
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float h_luminance, float photo_render, |
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int search_window = 21, |
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int block_size = 7, |
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Stream& stream = Stream::Null()); |
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CV_WRAP inline void fastNlMeansDenoisingColored(const GpuMat& src, CV_OUT GpuMat& dst, |
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float h_luminance, float photo_render, |
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int search_window = 21, |
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int block_size = 7, |
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Stream& stream = Stream::Null()) |
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{ |
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fastNlMeansDenoisingColored(InputArray(src), OutputArray(dst), h_luminance, photo_render, search_window, block_size, stream); |
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} |
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//! @} photo |
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}} // namespace cv { namespace cuda { |
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#endif /* OPENCV_PHOTO_CUDA_HPP */
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