Because of the visual perceptions dependent of background light or gray value, image enhancement is most useful technique to get more information within the images.
Some Basics of Image Enhancement:
a. Histogram Modifications:
In this operation, pixel values are transformed to new values independent of another pixel values. Some of the operations are Identity transformation(S=C*r), Logarithmic operation (S=C*log(r+1), Inverse operations(S=L-r), Exponential operation(S=Cr^k).
b. Histrogram Equalizations:
In this operation, whatever be the probability distribution of the pixels, new distribution will be of equal probability distribution. In this operations new transfer function will be defined according to the new equalized distribution function.
Local histogram equalization operation is preferred for higher informative images than Global histogram equalization paying more cost for the equalization operations.
c. Histrogram Matching:
In this operation, new histogram will be given which could not be uniform or can be said random distribution. According to given probability distribution, transfer function should be determined. For this operation; simply given histogram distribution will be mapped to equalized distribution and given new distribution will also be mapped to equalized distribution. From the mapping, we can get inverse mapping function to given required distribution function.
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