rknn-toolkit2-v2.1.0-2024-08-08
/
rknpu2
/examples
/3rdparty
/opencv
/opencv-linux-aarch64
/include
/opencv2
/photo
/cuda.hpp
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| //M*/ | |
| 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 { | |