org.opencv.xphoto

## Class LearningBasedWB

- java.lang.Object
- - org.opencv.core.Algorithm
  - - org.opencv.xphoto.WhiteBalancer
    - - org.opencv.xphoto.LearningBasedWB

-     public class LearningBasedWB
      extends WhiteBalancer

  More sophisticated learning-based automatic white balance algorithm. As REF: GrayworldWB, this algorithm works by applying different gains to the input image channels, but their computation is a bit more involved compared to the simple gray-world assumption. More details about the algorithm can be found in CITE: Cheng2015 . To mask out saturated pixels this function uses only pixels that satisfy the following condition: \( \frac{\textrm{max}(R,G,B)}{\texttt{range_max_val}} < \texttt{saturation_thresh} \) Currently supports images of type REF: CV_8UC3 and REF: CV_16UC3.

- - ### Field Summary

    - ### Fields inherited from class org.opencv.core.Algorithm

      `nativeObj`

  - ### Constructor Summary

    Constructors
    Modifier | Constructor and Description
    --- | ---
    `protected` | `LearningBasedWB(long addr)`

  - ### Method Summary

    All Methods Static Methods Instance Methods Concrete Methods
    Modifier and Type | Method and Description
    --- | ---
    `static LearningBasedWB` | `__fromPtr__(long addr)`
    `void` | `extractSimpleFeatures(Mat src, Mat dst)` Implements the feature extraction part of the algorithm.
    `protected void` | `finalize()`
    `int` | `getHistBinNum()` Defines the size of one dimension of a three-dimensional RGB histogram that is used internally by the algorithm.
    `int` | `getRangeMaxVal()` Maximum possible value of the input image (e.g.
    `float` | `getSaturationThreshold()` Threshold that is used to determine saturated pixels, i.e.
    `void` | `setHistBinNum(int val)` getHistBinNum SEE: getHistBinNum
    `void` | `setRangeMaxVal(int val)` getRangeMaxVal SEE: getRangeMaxVal
    `void` | `setSaturationThreshold(float val)` getSaturationThreshold SEE: getSaturationThreshold

    - ### Methods inherited from class org.opencv.xphoto.WhiteBalancer

      `balanceWhite`

    - ### Methods inherited from class org.opencv.core.Algorithm

      `clear, empty, getDefaultName, getNativeObjAddr, save`

    - ### Methods inherited from class java.lang.Object

      `clone, equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

- - ### Constructor Detail

    - #### LearningBasedWB

          protected LearningBasedWB(long addr)

  - ### Method Detail

    - #### __fromPtr__

          public static LearningBasedWB __fromPtr__(long addr)

    - #### getSaturationThreshold

          public float getSaturationThreshold()

      Threshold that is used to determine saturated pixels, i.e. pixels where at least one of the channels exceeds \(\texttt{saturation_threshold}\times\texttt{range_max_val}\) are ignored. SEE: setSaturationThreshold
      Returns:
        automatically generated

    - #### getHistBinNum

          public int getHistBinNum()

      Defines the size of one dimension of a three-dimensional RGB histogram that is used internally by the algorithm. It often makes sense to increase the number of bins for images with higher bit depth (e.g. 256 bins for a 12 bit image). SEE: setHistBinNum
      Returns:
        automatically generated

    - #### getRangeMaxVal

          public int getRangeMaxVal()

      Maximum possible value of the input image (e.g. 255 for 8 bit images, 4095 for 12 bit images) SEE: setRangeMaxVal
      Returns:
        automatically generated

    - #### extractSimpleFeatures

          public void extractSimpleFeatures(Mat src,
                                            Mat dst)

      Implements the feature extraction part of the algorithm. In accordance with CITE: Cheng2015 , computes the following features for the input image: 1. Chromaticity of an average (R,G,B) tuple 2. Chromaticity of the brightest (R,G,B) tuple (while ignoring saturated pixels) 3. Chromaticity of the dominant (R,G,B) tuple (the one that has the highest value in the RGB histogram) 4. Mode of the chromaticity palette, that is constructed by taking 300 most common colors according to the RGB histogram and projecting them on the chromaticity plane. Mode is the most high-density point of the palette, which is computed by a straightforward fixed-bandwidth kernel density estimator with a Epanechnikov kernel function.
      Parameters:
        `src` - Input three-channel image (BGR color space is assumed).
        `dst` - An array of four (r,g) chromaticity tuples corresponding to the features listed above.

    - #### setHistBinNum

          public void setHistBinNum(int val)

      getHistBinNum SEE: getHistBinNum
      Parameters:
        `val` - automatically generated

    - #### setRangeMaxVal

          public void setRangeMaxVal(int val)

      getRangeMaxVal SEE: getRangeMaxVal
      Parameters:
        `val` - automatically generated

    - #### setSaturationThreshold

          public void setSaturationThreshold(float val)

      getSaturationThreshold SEE: getSaturationThreshold
      Parameters:
        `val` - automatically generated

    - #### finalize

          protected void finalize()
                           throws Throwable

      Overrides:
        `finalize` in class `WhiteBalancer`
      Throws:
        `Throwable`

Generated on Thu Jul 25 2019 21:39:44 UTC / OpenCV 3.4.7