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OpenCV 2.4.3.1
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## org.opencv.photo
Class Photo

    java.lang.Object
      org.opencv.photo.Photo

    public class Photo

extends java.lang.Object

Field Summary
`static int` | `INPAINT_NS`
`static int` | `INPAINT_TELEA`

Constructor Summary
`Photo()`

Method Summary
`static void` | `fastNlMeansDenoising(Mat src, Mat dst)` Perform image denoising using Non-local Means Denoising algorithm http://www.ipol.im/pub/algo/bcm_non_local_means_denoising/ with several computational optimizations.
`static void` | `fastNlMeansDenoising(Mat src, Mat dst, float h, int templateWindowSize, int searchWindowSize)` Perform image denoising using Non-local Means Denoising algorithm http://www.ipol.im/pub/algo/bcm_non_local_means_denoising/ with several computational optimizations.
`static void` | `fastNlMeansDenoisingColored(Mat src, Mat dst)` Modification of `fastNlMeansDenoising` function for colored images The function converts image to CIELAB colorspace and then separately denoise L and AB components with given h parameters using `fastNlMeansDenoising` function.
`static void` | `fastNlMeansDenoisingColored(Mat src, Mat dst, float h, float hColor, int templateWindowSize, int searchWindowSize)` Modification of `fastNlMeansDenoising` function for colored images The function converts image to CIELAB colorspace and then separately denoise L and AB components with given h parameters using `fastNlMeansDenoising` function.
`static void` | `fastNlMeansDenoisingColoredMulti(java.util.List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize)` Modification of `fastNlMeansDenoisingMulti` function for colored images sequences The function converts images to CIELAB colorspace and then separately denoise L and AB components with given h parameters using `fastNlMeansDenoisingMulti` function.
`static void` | `fastNlMeansDenoisingColoredMulti(java.util.List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, float h, float hColor, int templateWindowSize, int searchWindowSize)` Modification of `fastNlMeansDenoisingMulti` function for colored images sequences The function converts images to CIELAB colorspace and then separately denoise L and AB components with given h parameters using `fastNlMeansDenoisingMulti` function.
`static void` | `fastNlMeansDenoisingMulti(java.util.List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize)` Modification of `fastNlMeansDenoising` function for images sequence where consequtive images have been captured in small period of time.
`static void` | `fastNlMeansDenoisingMulti(java.util.List<Mat> srcImgs, Mat dst, int imgToDenoiseIndex, int temporalWindowSize, float h, int templateWindowSize, int searchWindowSize)` Modification of `fastNlMeansDenoising` function for images sequence where consequtive images have been captured in small period of time.
`static void` | `inpaint(Mat src, Mat inpaintMask, Mat dst, double inpaintRadius, int flags)` Restores the selected region in an image using the region neighborhood.

Methods inherited from class java.lang.Object
`clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Field Detail

### INPAINT_NS

    public static final int INPAINT_NS

See Also:
  Constant Field Values

### INPAINT_TELEA

    public static final int INPAINT_TELEA

See Also:
  Constant Field Values

Constructor Detail

### Photo

    public Photo()

Method Detail

### fastNlMeansDenoising

    public static void fastNlMeansDenoising(Mat src,
                                            Mat dst)

  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

  This function expected to be applied to grayscale images. For colored images look at `fastNlMeansDenoisingColored`. Advanced usage of this functions can be manual denoising of colored image in different colorspaces. Such approach is used in `fastNlMeansDenoisingColored` by converting image to CIELAB colorspace and then separately denoise L and AB components with different h parameter.

  Parameters:
    `src` - Input 8-bit 1-channel, 2-channel or 3-channel image.
    `dst` - Output image with the same size and type as `src`.
  See Also:
    org.opencv.photo.Photo.fastNlMeansDenoising

### fastNlMeansDenoising

    public static void fastNlMeansDenoising(Mat src,
                                            Mat dst,
                                            float h,
                                            int templateWindowSize,
                                            int searchWindowSize)

  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

  This function expected to be applied to grayscale images. For colored images look at `fastNlMeansDenoisingColored`. Advanced usage of this functions can be manual denoising of colored image in different colorspaces. Such approach is used in `fastNlMeansDenoisingColored` by converting image to CIELAB colorspace and then separately denoise L and AB components with different h parameter.

  Parameters:
    `src` - Input 8-bit 1-channel, 2-channel or 3-channel image.
    `dst` - Output image with the same size and type as `src`.
    `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
    `templateWindowSize` - Size in pixels of the template patch that is used to compute weights. Should be odd. Recommended value 7 pixels
    `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 Also:
    org.opencv.photo.Photo.fastNlMeansDenoising

### fastNlMeansDenoisingColored

    public static void fastNlMeansDenoisingColored(Mat src,
                                                   Mat dst)

  Modification of `fastNlMeansDenoising` function for colored images

  The function converts image to CIELAB colorspace and then separately denoise L and AB components with given h parameters using `fastNlMeansDenoising` function.

  Parameters:
    `src` - Input 8-bit 3-channel image.
    `dst` - Output image with the same size and type as `src`.
  See Also:
    org.opencv.photo.Photo.fastNlMeansDenoisingColored

### fastNlMeansDenoisingColored

    public static void fastNlMeansDenoisingColored(Mat src,
                                                   Mat dst,
                                                   float h,
                                                   float hColor,
                                                   int templateWindowSize,
                                                   int searchWindowSize)

  Modification of `fastNlMeansDenoising` function for colored images

  The function converts image to CIELAB colorspace and then separately denoise L and AB components with given h parameters using `fastNlMeansDenoising` function.

  Parameters:
    `src` - Input 8-bit 3-channel image.
    `dst` - Output image with the same size and type as `src`.
    `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
    `hColor` - a hColor
    `templateWindowSize` - Size in pixels of the template patch that is used to compute weights. Should be odd. Recommended value 7 pixels
    `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 Also:
    org.opencv.photo.Photo.fastNlMeansDenoisingColored

### fastNlMeansDenoisingColoredMulti

    public static void fastNlMeansDenoisingColoredMulti(java.util.List<Mat> srcImgs,
                                                        Mat dst,
                                                        int imgToDenoiseIndex,
                                                        int temporalWindowSize)

  Modification of `fastNlMeansDenoisingMulti` function for colored images sequences

  The function converts images to CIELAB colorspace and then separately denoise L and AB components with given h parameters using `fastNlMeansDenoisingMulti` function.

  Parameters:
    `srcImgs` - Input 8-bit 3-channel images sequence. All images should have the same type and size.
    `dst` - Output image with the same size and type as `srcImgs` images.
    `imgToDenoiseIndex` - Target image to denoise index in `srcImgs` sequence
    `temporalWindowSize` - Number of surrounding images to use for target image denoising. Should be odd. Images from `imgToDenoiseIndex - temporalWindowSize / 2` to `imgToDenoiseIndex - temporalWindowSize / 2` from `srcImgs` will be used to denoise `srcImgs[imgToDenoiseIndex]` image.
  See Also:
    org.opencv.photo.Photo.fastNlMeansDenoisingColoredMulti

### fastNlMeansDenoisingColoredMulti

    public static void fastNlMeansDenoisingColoredMulti(java.util.List<Mat> srcImgs,
                                                        Mat dst,
                                                        int imgToDenoiseIndex,
                                                        int temporalWindowSize,
                                                        float h,
                                                        float hColor,
                                                        int templateWindowSize,
                                                        int searchWindowSize)

  Modification of `fastNlMeansDenoisingMulti` function for colored images sequences

  The function converts images to CIELAB colorspace and then separately denoise L and AB components with given h parameters using `fastNlMeansDenoisingMulti` function.

  Parameters:
    `srcImgs` - Input 8-bit 3-channel images sequence. All images should have the same type and size.
    `dst` - Output image with the same size and type as `srcImgs` images.
    `imgToDenoiseIndex` - Target image to denoise index in `srcImgs` sequence
    `temporalWindowSize` - Number of surrounding images to use for target image denoising. Should be odd. Images from `imgToDenoiseIndex - temporalWindowSize / 2` to `imgToDenoiseIndex - temporalWindowSize / 2` from `srcImgs` will be used to denoise `srcImgs[imgToDenoiseIndex]` image.
    `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.
    `hColor` - a hColor
    `templateWindowSize` - Size in pixels of the template patch that is used to compute weights. Should be odd. Recommended value 7 pixels
    `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 Also:
    org.opencv.photo.Photo.fastNlMeansDenoisingColoredMulti

### fastNlMeansDenoisingMulti

    public static void fastNlMeansDenoisingMulti(java.util.List<Mat> srcImgs,
                                                 Mat dst,
                                                 int imgToDenoiseIndex,
                                                 int temporalWindowSize)

  Modification of `fastNlMeansDenoising` 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

  Parameters:
    `srcImgs` - Input 8-bit 1-channel, 2-channel or 3-channel images sequence. All images should have the same type and size.
    `dst` - Output image with the same size and type as `srcImgs` images.
    `imgToDenoiseIndex` - Target image to denoise index in `srcImgs` sequence
    `temporalWindowSize` - Number of surrounding images to use for target image denoising. Should be odd. Images from `imgToDenoiseIndex - temporalWindowSize / 2` to `imgToDenoiseIndex - temporalWindowSize / 2` from `srcImgs` will be used to denoise `srcImgs[imgToDenoiseIndex]` image.
  See Also:
    org.opencv.photo.Photo.fastNlMeansDenoisingMulti

### fastNlMeansDenoisingMulti

    public static void fastNlMeansDenoisingMulti(java.util.List<Mat> srcImgs,
                                                 Mat dst,
                                                 int imgToDenoiseIndex,
                                                 int temporalWindowSize,
                                                 float h,
                                                 int templateWindowSize,
                                                 int searchWindowSize)

  Modification of `fastNlMeansDenoising` 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

  Parameters:
    `srcImgs` - Input 8-bit 1-channel, 2-channel or 3-channel images sequence. All images should have the same type and size.
    `dst` - Output image with the same size and type as `srcImgs` images.
    `imgToDenoiseIndex` - Target image to denoise index in `srcImgs` sequence
    `temporalWindowSize` - Number of surrounding images to use for target image denoising. Should be odd. Images from `imgToDenoiseIndex - temporalWindowSize / 2` to `imgToDenoiseIndex - temporalWindowSize / 2` from `srcImgs` will be used to denoise `srcImgs[imgToDenoiseIndex]` image.
    `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
    `templateWindowSize` - Size in pixels of the template patch that is used to compute weights. Should be odd. Recommended value 7 pixels
    `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 Also:
    org.opencv.photo.Photo.fastNlMeansDenoisingMulti

### inpaint

    public static void inpaint(Mat src,
                               Mat inpaintMask,
                               Mat dst,
                               double inpaintRadius,
                               int flags)

  Restores the selected region in an image using the region neighborhood.

  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.

  Parameters:
    `src` - Input 8-bit 1-channel or 3-channel image.
    `inpaintMask` - Inpainting mask, 8-bit 1-channel image. Non-zero pixels indicate the area that needs to be inpainted.
    `dst` - Output image with the same size and type as `src`.
    `inpaintRadius` - Radius of a circular neighborhood of each point inpainted that is considered by the algorithm.
    `flags` - Inpainting method that could be one of the following:
    - INPAINT_NS Navier-Stokes based method.
    - INPAINT_TELEA Method by Alexandru Telea [Telea04].
  See Also:
    org.opencv.photo.Photo.inpaint

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