A Computational Introduction to Digital Image Processing, 2nd Edition

82 A Computational Introduction to Digital Image Processing, Second Edition

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FIGURE 4.22: The cumulative histogram

As we have seen, none of the example histograms, after equalization, are uniform. This

is a result of the discrete nature of the image. If we were to treat the image as a continuous

function f(x, y), and the histogram as the area between different contours (see, for example,

Castleman [7]), then we can treat the histogram as a probability density function. But the

corresponding cumulative density function will always have a uniform histogram; see, for

example, Hogg and Craig [17].

4.4 ...