Histogram equalization is a specific case of the more general class of histogram remapping methods. V-optimal histograms are an example of a more "exotic" histogram. The total area of a histogram used for probability density is always normalized to 1. The gradient orientations are quantized in 16 bins resulting in 272-bin histogram. It can be viewed as a generalisation of histogram density estimation with improved statistical properties. Histogram equalization is best method for image enhancement. A sample is categorized by its amplitude into one of 32 bands (histogram bins). Normalization is sometimes called contrast stretching or histogram stretching. This proposed processing includes filtering, histogram truncation and equalization steps. And the 2-dimensional Otsu's method is developed based on the 2-dimensional histogram as follows. The values of a color histogram are from statistics. The total area of the histogram is equal to the number of data. Image editors have provisions to create an image histogram of the image being edited. The peaks in this histogram correspond to dominant orientations. The mode is then the value where the histogram reaches its peak.