Histogram conversion is the conversion of the histogram of original image to an other histogram. Histogram conversion can be said to be a type of gray scale conversion.
There are two typical histogram conversion techniques.
a. Histogram equalization
Histogram equalization is to convert the histogram of an original image to equalized histogram as shown in Figure 10.3.1. As a first step, an accumulated histogram should be made. Then the accumulated histogram should be divided into a number of equal regions. Thirdly , the corresponding gray scale in each region should be assigned to a converted gray scale.
The effect of histogram equalization is that parts of the image with more frequency variation will be more enhanced, while parts of an image with less frequency will be neglected.
Figure 10.3.2 shows a comparison between the original image and the converted image, after histogram equalization.
b. Histogram normalization
Generally a normal distribution of the density in an image would create an image that is natural for a human observation. In this sense the histogram of the original image may be sometimes converted to the normalized histogram. However in this conversion, pixels with same gray scale should be reallocated to other pixels with a different gray scales, in order to form a normalized histogram.
Therefore such a gray scale conversion is not a 1:1 conversion and thus enables no reverse conversion. Histogram normalization may be applied, for example, to an unfocused image of a planet with a low dynamic range, though it is not be very much popular for ordinary remote sensing data.
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