How can I calculate normalized histogram from some squared regions of an image?

I have three squared sized regions, which are cropped from a gray scale image. The size of each region is K by K. How can I calculate normalized histogram from the cropped regions and display the histogram like the following figure, which I have shown below.....

Answer 1

[Image Analyst]

Can't you just use histogram with the 'pdf' or 'probability' option?

[K M Ibrahim Khalilullah]

Sorry, I can't understand your question. would you explain please about your question and probability option?

[Image Analyst]

From the help:

Description

histogram(X) creates a histogram plot of X. The histogram function uses an automatic binning algorithm that returns bins with a uniform width, chosen to cover the range of elements in X and reveal the underlying shape of the distribution. histogram displays the bins as rectangles such that the height of each rectangle indicates the number of elements in the bin.

'probability': The height of each bar is the relative number of observations, (number of observations in bin / total number of observations). The sum of the bar heights is 1. For categorical histograms, the height of each bar is, (number of elements in category / total number of elements in all categories). The sum of the bar heights is 1.

'pdf': Probability density function estimate. The height of each bar is, (number of observations in the bin) / (total number of observations * width of bin). The area of each bar is the relative number of observations. The sum of the bar areas is 1. For categorical histograms, this is the same as 'probability'.

[K M Ibrahim Khalilullah]

Thank you very much. I understand. would you explain please how can I combine three different squared regions to make X?