for (int Y = 0; Y < 256; Y++){if (Y < Min)Table[Y] = 0;else if (Y > Max)Table[Y] = 255;elseTable[Y] = IM_ClampToByte((float)(Y - Min) / (Max - Min) * 255);}

    float Avg = 0, Mean = 0, Sum = 0;for (int Y = 0; Y < 256; Y++){Sum += Histgram[Y];Avg += Y * Histgram[Y];}Mean = Avg / Sum;float Gamma = log(0.5f) / log((float)(Mean - Min) / (Max - Min));if (Gamma < 0.1f)Gamma = 0.1f;else if (Gamma > 10)Gamma = 10;for (int Y = 0; Y < 256; Y++){if (Y < Min)Table[Y] = 0;else if (Y > Max)Table[Y] = 255;elseTable[Y] = IM_ClampToByte(pow((float)(Y - Min) / (Max - Min), Gamma) * 255);}

//    Changes the tone curves of images.
//    It should bring up the detail in the flat regions of your image.
//    Histogram Equalization can enhance meaningless detail and hide important but small high-contrast features. This method uses a
//    similar algorithm, but uses the square root of the histogram values, so its effects are less extreme. Hold the alt key down
//    to use the standard histogram equalization algorithm. This code was contributed by Richard Kirk (rak@cre.canon.co.uk).
//    ImageJ\source\ij\plugin\ContrastEnhancer.java

private void equalize(ImageProcessor ip, int[] histogram)
{ip.resetRoi();if (ip instanceof ShortProcessor) {  // Shortmax = 65535;range = 65535;} else { //bytesmax = 255;range = 255;}double sum;sum = getWeightedValue(histogram, 0);for (int i=1; i<max; i++)sum += 2 * getWeightedValue(histogram, i);sum += getWeightedValue(histogram, max);double scale = range/sum;int[] lut = new int[range+1];lut[0] = 0;sum = getWeightedValue(histogram, 0);for (int i=1; i<max; i++) {double delta = getWeightedValue(histogram, i);sum += delta;lut[i] = (int)Math.round(sum*scale);sum += delta;}lut[max] = max;applyTable(ip, lut);
}

private double getWeightedValue(int[] histogram, int i) {int h = histogram[i];if (h<2 || classicEqualization) return (double)h;return Math.sqrt((double)(h));
}