OpenCVForUnity/package/Runtime/Plugins/iOS/opencv2.framework/Headers/photo/cuda.hpp

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#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());
CV_WRAP inline void nonLocalMeans(const GpuMat& src, CV_OUT GpuMat& dst,
                            float h,
                            int search_window = 21,
                            int block_size = 7,
                            int borderMode = BORDER_DEFAULT,
                            Stream& stream = Stream::Null())
{
    nonLocalMeans(InputArray(src), OutputArray(dst), h, search_window, block_size, borderMode, stream);
};

/** @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());
CV_WRAP inline void fastNlMeansDenoising(const GpuMat& src, CV_OUT GpuMat& dst,
                                    float h,
                                    int search_window = 21,
                                    int block_size = 7,
                                    Stream& stream = Stream::Null())
{
    fastNlMeansDenoising(InputArray(src), OutputArray(dst), h, search_window, block_size, stream);
}

/** @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());
CV_WRAP inline void fastNlMeansDenoisingColored(const GpuMat& src, CV_OUT GpuMat& dst,
                                            float h_luminance, float photo_render,
                                            int search_window = 21,
                                            int block_size = 7,
                                            Stream& stream = Stream::Null())
{
    fastNlMeansDenoisingColored(InputArray(src), OutputArray(dst), h_luminance, photo_render, search_window, block_size, stream);
}

//! @} photo

}} // namespace cv { namespace cuda {

#endif /* OPENCV_PHOTO_CUDA_HPP */