Image pixel value statistics

  • Maximum, minimum and position of image pixels
  • Image mean and standard deviation

Find maximum and minimum values

API

public static MinMaxLocResult minMaxLoc(Mat src, Mat mask)

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  • Parameter SRC: input image matrix

  • Parameter mask: Optional mask matrix

  • Return value MinMaxLocResult: Records the minimum value, maximum value, and their positions

    public static class MinMaxLocResult {

        public double minVal;

        public double maxVal;

        public Point minLoc;

        public Point maxLoc;





        public MinMaxLocResult(a) {

            minVal=0; maxVal=0;

            minLoc=new Point();

            maxLoc=new Point();

        }

    }

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  • The function requires that the input image must be single channel

Find the maximum and minimum values of the image matrix and their positions

Since only a single channel image can be entered, the calculation operation is performed after separation

private fun minMaxLoc(source: Mat) {

    val bgrList = ArrayList<Mat>()

    Core.split(source, bgrList)



    var minLoc = Point()

    var maxLoc = Point()

    var minVal = 255.0

    var maxVal = 0.0

    var minCha = 0

    var maxCha = 0

    for (index in 0 until bgrList.size) {

        val tmp = Core.minMaxLoc(bgrList[index])

        if (tmp.minVal < minVal) {

            minVal = tmp.minVal

            minLoc = tmp.minLoc

            minCha = index

        }

        if (tmp.maxVal > maxVal) {

            maxVal = tmp.maxVal

            maxLoc = tmp.maxLoc

            maxCha = index

        }

    }

    val tmp =

        "Minimum =$minVal, located in the${minCha}channel${minLoc}\n Maximum value =$maxVal, located in the${maxCha}channel${maxLoc}\n"

    message += tmp



    for (current in bgrList) {

        current.release()

    }

}

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Mean and standard deviation

concept

  • The mean value reflects the brightness of the image. The greater the mean value is, the greater the brightness of the image is, and vice versa.


  • The standard deviation, also known as the mean square error, is the square root of the arithmetic mean of the square of the mean deviation, denoted by σ. It is most commonly used in probability statistics as a measure of the degree of statistical distribution. Standard deviation is the arithmetic square root of variance. Standard deviation can reflect the degree of dispersion of a data set. Standard deviation reflects the degree of dispersion between the pixel value and the mean value of the image. The larger the standard deviation is, the better the quality of the image is.


API

public static void meanStdDev(Mat src, MatOfDouble mean, MatOfDouble stddev, Mat mask)

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  • Parameter SRC: input image matrix
  • Parameter mean: output image pixel mean matrix
  • Parameter stddev: J-matrix of output image pixel variance
  • Parameter mask: Optional mask matrix

Calculate the mean and standard deviation of the image matrix

private fun meanStdDev(source: Mat) {

    val mean = MatOfDouble()

    val stdDev = MatOfDouble()

    Core.meanStdDev(source, mean, stdDev)

    val tmp = "Average value:${mean.toList()}\ n variance:${stdDev.toList()}\n"

    message += tmp

    mean.release()

    stdDev.release()

}

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The calculation results


The source code

https://github.com/onlyloveyd/LearningAndroidOpenCV


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