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- /*M///////////////////////////////////////////////////////////////////////////////////////
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- // For Open Source Computer Vision Library
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- //M*/
- #ifndef OPENCV_PHOTO_CUDA_HPP
- #define OPENCV_PHOTO_CUDA_HPP
- #include "opencv2/core/cuda.hpp"
- namespace cv { namespace cuda {
- //! @addtogroup photo_denoise
- //! @{
- /** @brief Performs pure non local means denoising without any simplification, and thus it is not fast.
- @param src Source image. Supports only CV_8UC1, CV_8UC2 and CV_8UC3.
- @param dst Destination image.
- @param h Filter sigma regulating filter strength for color.
- @param search_window Size of search window.
- @param block_size Size of block used for computing weights.
- @param borderMode Border type. See borderInterpolate for details. BORDER_REFLECT101 ,
- BORDER_REPLICATE , BORDER_CONSTANT , BORDER_REFLECT and BORDER_WRAP are supported for now.
- @param stream Stream for the asynchronous version.
- @sa
- fastNlMeansDenoising
- */
- CV_EXPORTS void nonLocalMeans(InputArray src, OutputArray dst,
- float h,
- int search_window = 21,
- int block_size = 7,
- int borderMode = BORDER_DEFAULT,
- Stream& stream = Stream::Null());
- /** @brief Perform image denoising using Non-local Means Denoising algorithm
- <http://www.ipol.im/pub/algo/bcm_non_local_means_denoising> with several computational
- optimizations. Noise expected to be a gaussian white noise
- @param src Input 8-bit 1-channel, 2-channel or 3-channel image.
- @param dst Output image with the same size and type as src .
- @param h Parameter regulating filter strength. Big h value perfectly removes noise but also
- removes image details, smaller h value preserves details but also preserves some noise
- @param search_window Size in pixels of the window that is used to compute weighted average for
- given pixel. Should be odd. Affect performance linearly: greater search_window - greater
- denoising time. Recommended value 21 pixels
- @param block_size Size in pixels of the template patch that is used to compute weights. Should be
- odd. Recommended value 7 pixels
- @param stream Stream for the asynchronous invocations.
- This function expected to be applied to grayscale images. For colored images look at
- FastNonLocalMeansDenoising::labMethod.
- @sa
- fastNlMeansDenoising
- */
- CV_EXPORTS void fastNlMeansDenoising(InputArray src, OutputArray dst,
- float h,
- int search_window = 21,
- int block_size = 7,
- Stream& stream = Stream::Null());
- /** @brief Modification of fastNlMeansDenoising function for colored images
- @param src Input 8-bit 3-channel image.
- @param dst Output image with the same size and type as src .
- @param h_luminance Parameter regulating filter strength. Big h value perfectly removes noise but
- also removes image details, smaller h value preserves details but also preserves some noise
- @param photo_render float The same as h but for color components. For most images value equals 10 will be
- enough to remove colored noise and do not distort colors
- @param search_window Size in pixels of the window that is used to compute weighted average for
- given pixel. Should be odd. Affect performance linearly: greater search_window - greater
- denoising time. Recommended value 21 pixels
- @param block_size Size in pixels of the template patch that is used to compute weights. Should be
- odd. Recommended value 7 pixels
- @param stream Stream for the asynchronous invocations.
- The function converts image to CIELAB colorspace and then separately denoise L and AB components
- with given h parameters using FastNonLocalMeansDenoising::simpleMethod function.
- @sa
- fastNlMeansDenoisingColored
- */
- CV_EXPORTS void fastNlMeansDenoisingColored(InputArray src, OutputArray dst,
- float h_luminance, float photo_render,
- int search_window = 21,
- int block_size = 7,
- Stream& stream = Stream::Null());
- //! @} photo
- }} // namespace cv { namespace cuda {
- #endif /* OPENCV_PHOTO_CUDA_HPP */
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