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// // This file is auto-generated. Please don't modify it! ////w w w.java 2 s. c o m package org.opencv.photo; import java.util.List; import org.opencv.core.Mat; import org.opencv.utils.Converters; public class Photo { private static final int CV_INPAINT_NS = 0, CV_INPAINT_TELEA = 1; public static final int INPAINT_NS = CV_INPAINT_NS, INPAINT_TELEA = CV_INPAINT_TELEA; // // C++: void fastNlMeansDenoising(Mat src, Mat& dst, float h = 3, int templateWindowSize = 7, int searchWindowSize = 21) // /** * <p>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</p> * * <p>This function expected to be applied to grayscale images. For colored images * look at <code>fastNlMeansDenoisingColored</code>. * Advanced usage of this functions can be manual denoising of colored image in * different colorspaces. * Such approach is used in <code>fastNlMeansDenoisingColored</code> by * converting image to CIELAB colorspace and then separately denoise L and AB * components with different h parameter.</p> * * @param src Input 8-bit 1-channel, 2-channel or 3-channel image. * @param dst Output image with the same size and type as <code>src</code>. * @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 templateWindowSize Size in pixels of the template patch that is used * to compute weights. Should be odd. Recommended value 7 pixels * @param searchWindowSize Size in pixels of the window that is used to compute * weighted average for given pixel. Should be odd. Affect performance linearly: * greater searchWindowsSize - greater denoising time. Recommended value 21 * pixels * * @see <a href="http://docs.opencv.org/modules/photo/doc/denoising.html#fastnlmeansdenoising">org.opencv.photo.Photo.fastNlMeansDenoising</a> */ public static void fastNlMeansDenoising(Mat src, Mat dst, float h, int templateWindowSize, int searchWindowSize) { fastNlMeansDenoising_0(src.nativeObj, dst.nativeObj, h, templateWindowSize, searchWindowSize); return; } /** * <p>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</p> * * <p>This function expected to be applied to grayscale images. For colored images * look at <code>fastNlMeansDenoisingColored</code>. * Advanced usage of this functions can be manual denoising of colored image in * different colorspaces. * Such approach is used in <code>fastNlMeansDenoisingColored</code> by * converting image to CIELAB colorspace and then separately denoise L and AB * components with different h parameter.</p> * * @param src Input 8-bit 1-channel, 2-channel or 3-channel image. * @param dst Output image with the same size and type as <code>src</code>. * * @see <a href="http://docs.opencv.org/modules/photo/doc/denoising.html#fastnlmeansdenoising">org.opencv.photo.Photo.fastNlMeansDenoising</a> */ public static void fastNlMeansDenoising(Mat src, Mat dst) { fastNlMeansDenoising_1(src.nativeObj, dst.nativeObj); return; } // // C++: void fastNlMeansDenoisingColored(Mat src, Mat& dst, float h = 3, float hColor = 3, int templateWindowSize = 7, int searchWindowSize = 21) // /** * <p>Modification of <code>fastNlMeansDenoising</code> function for colored images</p> * * <p>The function converts image to CIELAB colorspace and then separately denoise * L and AB components with given h parameters using <code>fastNlMeansDenoising</code> * function.</p> * * @param src Input 8-bit 3-channel image. * @param dst Output image with the same size and type as <code>src</code>. * @param h Parameter regulating filter strength for luminance component. Bigger * h value perfectly removes noise but also removes image details, smaller h * value preserves details but also preserves some noise * @param hColor a hColor * @param templateWindowSize Size in pixels of the template patch that is used * to compute weights. Should be odd. Recommended value 7 pixels * @param searchWindowSize Size in pixels of the window that is used to compute * weighted average for given pixel. Should be odd. Affect performance linearly: * greater searchWindowsSize - greater denoising time. Recommended value 21 * pixels * * @see <a href="http://docs.opencv.org/modules/photo/doc/denoising.html#fastnlmeansdenoisingcolored">org.opencv.photo.Photo.fastNlMeansDenoisingColored</a> */ public static void fastNlMeansDenoisingColored(Mat src, Mat dst, float h, float hColor, int templateWindowSize, int searchWindowSize) { fastNlMeansDenoisingColored_0(src.nativeObj, dst.nativeObj, h, hColor, templateWindowSize, searchWindowSize); return; } /** * <p>Modification of <code>fastNlMeansDenoising</code> function for colored images</p> * * <p>The function converts image to CIELAB colorspace and then separately denoise * L and AB components with given h parameters using <code>fastNlMeansDenoising</code> * function.</p> * * @param src Input 8-bit 3-channel image. * @param dst Output image with the same size and type as <code>src</code>. * * @see <a href="http://docs.opencv.org/modules/photo/doc/denoising.html#fastnlmeansdenoisingcolored">org.opencv.photo.Photo.fastNlMeansDenoisingColored</a> */ public static void fastNlMeansDenoisingColored(Mat src, Mat dst) { fastNlMeansDenoisingColored_1(src.nativeObj, dst.nativeObj); return; } // // C++: void fastNlMeansDenoisingColoredMulti(vector_Mat srcImgs, Mat& dst, int imgToDenoiseIndex, int temporalWindowSize, float h = 3, float hColor = 3, int templateWindowSize = 7, int searchWindowSize = 21) // /** * <p>Modification of <code>fastNlMeansDenoisingMulti</code> function for colored * images sequences</p> * * <p>The function converts images to CIELAB colorspace and then separately denoise * L and AB components with given h parameters using <code>fastNlMeansDenoisingMulti</code> * function.</p> * * @param srcImgs Input 8-bit 3-channel images sequence. All images should have * the same type and size. * @param dst Output image with the same size and type as <code>srcImgs</code> * images. * @param imgToDenoiseIndex Target image to denoise index in <code>srcImgs</code> * sequence * @param temporalWindowSize Number of surrounding images to use for target * image denoising. Should be odd. Images from <code>imgToDenoiseIndex - * temporalWindowSize / 2</code> to <code>imgToDenoiseIndex - temporalWindowSize * / 2</code> from <code>srcImgs</code> will be used to denoise * <code>srcImgs[imgToDenoiseIndex]</code> image. * @param h Parameter regulating filter strength for luminance component. Bigger * h value perfectly removes noise but also removes image details, smaller h * value preserves details but also preserves some noise. * @param hColor a hColor * @param templateWindowSize Size in pixels of the template patch that is used * to compute weights. Should be odd. Recommended value 7 pixels * @param searchWindowSize Size in pixels of the window that is used to compute * weighted average for given pixel. Should be odd. Affect performance linearly: * greater searchWindowsSize - greater denoising time. Recommended value 21 * pixels * * @see <a href="http://docs.opencv.org/modules/photo/doc/denoising.html#fastnlmeansdenoisingcoloredmulti">org.opencv.photo.Photo.fastNlMeansDenoisingColoredMulti</a> */ public static void fastNlMeansDenoisingColoredMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, float h, float hColor, int templateWindowSize, int searchWindowSize) { Mat srcImgs_mat = Converters.vector_Mat_to_Mat(srcImgs); fastNlMeansDenoisingColoredMulti_0(srcImgs_mat.nativeObj, dst.nativeObj, imgToDenoiseIndex, temporalWindowSize, h, hColor, templateWindowSize, searchWindowSize); return; } /** * <p>Modification of <code>fastNlMeansDenoisingMulti</code> function for colored * images sequences</p> * * <p>The function converts images to CIELAB colorspace and then separately denoise * L and AB components with given h parameters using <code>fastNlMeansDenoisingMulti</code> * function.</p> * * @param srcImgs Input 8-bit 3-channel images sequence. All images should have * the same type and size. * @param dst Output image with the same size and type as <code>srcImgs</code> * images. * @param imgToDenoiseIndex Target image to denoise index in <code>srcImgs</code> * sequence * @param temporalWindowSize Number of surrounding images to use for target * image denoising. Should be odd. Images from <code>imgToDenoiseIndex - * temporalWindowSize / 2</code> to <code>imgToDenoiseIndex - temporalWindowSize * / 2</code> from <code>srcImgs</code> will be used to denoise * <code>srcImgs[imgToDenoiseIndex]</code> image. * * @see <a href="http://docs.opencv.org/modules/photo/doc/denoising.html#fastnlmeansdenoisingcoloredmulti">org.opencv.photo.Photo.fastNlMeansDenoisingColoredMulti</a> */ public static void fastNlMeansDenoisingColoredMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize) { Mat srcImgs_mat = Converters.vector_Mat_to_Mat(srcImgs); fastNlMeansDenoisingColoredMulti_1(srcImgs_mat.nativeObj, dst.nativeObj, imgToDenoiseIndex, temporalWindowSize); return; } // // C++: void fastNlMeansDenoisingMulti(vector_Mat srcImgs, Mat& dst, int imgToDenoiseIndex, int temporalWindowSize, float h = 3, int templateWindowSize = 7, int searchWindowSize = 21) // /** * <p>Modification of <code>fastNlMeansDenoising</code> function for images * sequence where consequtive images have been captured in small period of time. * For example video. This version of the function is for grayscale images or * for manual manipulation with colorspaces. * For more details see http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.131.6394</p> * * @param srcImgs Input 8-bit 1-channel, 2-channel or 3-channel images sequence. * All images should have the same type and size. * @param dst Output image with the same size and type as <code>srcImgs</code> * images. * @param imgToDenoiseIndex Target image to denoise index in <code>srcImgs</code> * sequence * @param temporalWindowSize Number of surrounding images to use for target * image denoising. Should be odd. Images from <code>imgToDenoiseIndex - * temporalWindowSize / 2</code> to <code>imgToDenoiseIndex - temporalWindowSize * / 2</code> from <code>srcImgs</code> will be used to denoise * <code>srcImgs[imgToDenoiseIndex]</code> image. * @param h Parameter regulating filter strength for luminance component. Bigger * h value perfectly removes noise but also removes image details, smaller h * value preserves details but also preserves some noise * @param templateWindowSize Size in pixels of the template patch that is used * to compute weights. Should be odd. Recommended value 7 pixels * @param searchWindowSize Size in pixels of the window that is used to compute * weighted average for given pixel. Should be odd. Affect performance linearly: * greater searchWindowsSize - greater denoising time. Recommended value 21 * pixels * * @see <a href="http://docs.opencv.org/modules/photo/doc/denoising.html#fastnlmeansdenoisingmulti">org.opencv.photo.Photo.fastNlMeansDenoisingMulti</a> */ public static void fastNlMeansDenoisingMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, float h, int templateWindowSize, int searchWindowSize) { Mat srcImgs_mat = Converters.vector_Mat_to_Mat(srcImgs); fastNlMeansDenoisingMulti_0(srcImgs_mat.nativeObj, dst.nativeObj, imgToDenoiseIndex, temporalWindowSize, h, templateWindowSize, searchWindowSize); return; } /** * <p>Modification of <code>fastNlMeansDenoising</code> function for images * sequence where consequtive images have been captured in small period of time. * For example video. This version of the function is for grayscale images or * for manual manipulation with colorspaces. * For more details see http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.131.6394</p> * * @param srcImgs Input 8-bit 1-channel, 2-channel or 3-channel images sequence. * All images should have the same type and size. * @param dst Output image with the same size and type as <code>srcImgs</code> * images. * @param imgToDenoiseIndex Target image to denoise index in <code>srcImgs</code> * sequence * @param temporalWindowSize Number of surrounding images to use for target * image denoising. Should be odd. Images from <code>imgToDenoiseIndex - * temporalWindowSize / 2</code> to <code>imgToDenoiseIndex - temporalWindowSize * / 2</code> from <code>srcImgs</code> will be used to denoise * <code>srcImgs[imgToDenoiseIndex]</code> image. * * @see <a href="http://docs.opencv.org/modules/photo/doc/denoising.html#fastnlmeansdenoisingmulti">org.opencv.photo.Photo.fastNlMeansDenoisingMulti</a> */ public static void fastNlMeansDenoisingMulti(List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize) { Mat srcImgs_mat = Converters.vector_Mat_to_Mat(srcImgs); fastNlMeansDenoisingMulti_1(srcImgs_mat.nativeObj, dst.nativeObj, imgToDenoiseIndex, temporalWindowSize); return; } // // C++: void inpaint(Mat src, Mat inpaintMask, Mat& dst, double inpaintRadius, int flags) // /** * <p>Restores the selected region in an image using the region neighborhood.</p> * * <p>The function reconstructs the selected image area from the pixel near the * area boundary. The function may be used to remove dust and scratches from a * scanned photo, or to remove undesirable objects from still images or video. * See http://en.wikipedia.org/wiki/Inpainting for more details.</p> * * <p>Note:</p> * <ul> * <li> An example using the inpainting technique can be found at * opencv_source_code/samples/cpp/inpaint.cpp * <li> (Python) An example using the inpainting technique can be found at * opencv_source_code/samples/python2/inpaint.py * </ul> * * @param src Input 8-bit 1-channel or 3-channel image. * @param inpaintMask Inpainting mask, 8-bit 1-channel image. Non-zero pixels * indicate the area that needs to be inpainted. * @param dst Output image with the same size and type as <code>src</code>. * @param inpaintRadius Radius of a circular neighborhood of each point * inpainted that is considered by the algorithm. * @param flags Inpainting method that could be one of the following: * <ul> * <li> INPAINT_NS Navier-Stokes based method. * <li> INPAINT_TELEA Method by Alexandru Telea [Telea04]. * </ul> * * @see <a href="http://docs.opencv.org/modules/photo/doc/inpainting.html#inpaint">org.opencv.photo.Photo.inpaint</a> */ public static void inpaint(Mat src, Mat inpaintMask, Mat dst, double inpaintRadius, int flags) { inpaint_0(src.nativeObj, inpaintMask.nativeObj, dst.nativeObj, inpaintRadius, flags); return; } // C++: void fastNlMeansDenoising(Mat src, Mat& dst, float h = 3, int templateWindowSize = 7, int searchWindowSize = 21) private static native void fastNlMeansDenoising_0(long src_nativeObj, long dst_nativeObj, float h, int templateWindowSize, int searchWindowSize); private static native void fastNlMeansDenoising_1(long src_nativeObj, long dst_nativeObj); // C++: void fastNlMeansDenoisingColored(Mat src, Mat& dst, float h = 3, float hColor = 3, int templateWindowSize = 7, int searchWindowSize = 21) private static native void fastNlMeansDenoisingColored_0(long src_nativeObj, long dst_nativeObj, float h, float hColor, int templateWindowSize, int searchWindowSize); private static native void fastNlMeansDenoisingColored_1(long src_nativeObj, long dst_nativeObj); // C++: void fastNlMeansDenoisingColoredMulti(vector_Mat srcImgs, Mat& dst, int imgToDenoiseIndex, int temporalWindowSize, float h = 3, float hColor = 3, int templateWindowSize = 7, int searchWindowSize = 21) private static native void fastNlMeansDenoisingColoredMulti_0(long srcImgs_mat_nativeObj, long dst_nativeObj, int imgToDenoiseIndex, int temporalWindowSize, float h, float hColor, int templateWindowSize, int searchWindowSize); private static native void fastNlMeansDenoisingColoredMulti_1(long srcImgs_mat_nativeObj, long dst_nativeObj, int imgToDenoiseIndex, int temporalWindowSize); // C++: void fastNlMeansDenoisingMulti(vector_Mat srcImgs, Mat& dst, int imgToDenoiseIndex, int temporalWindowSize, float h = 3, int templateWindowSize = 7, int searchWindowSize = 21) private static native void fastNlMeansDenoisingMulti_0(long srcImgs_mat_nativeObj, long dst_nativeObj, int imgToDenoiseIndex, int temporalWindowSize, float h, int templateWindowSize, int searchWindowSize); private static native void fastNlMeansDenoisingMulti_1(long srcImgs_mat_nativeObj, long dst_nativeObj, int imgToDenoiseIndex, int temporalWindowSize); // C++: void inpaint(Mat src, Mat inpaintMask, Mat& dst, double inpaintRadius, int flags) private static native void inpaint_0(long src_nativeObj, long inpaintMask_nativeObj, long dst_nativeObj, double inpaintRadius, int flags); }