Package org.opencv.xphoto

Class 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.

    • Constructor Detail

      • LearningBasedWB

        protected LearningBasedWB​(long addr)

    • Method Detail

      • 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 java.lang.Throwable
        Overrides:
        finalize in class WhiteBalancer
        Throws:
        java.lang.Throwable