November 2018
Intermediate to advanced
492 pages
12h 19m
English
Content preview from Hands-On Image Processing with Python
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Histogram processing – histogram equalization and matching
Histogram processing techniques provide a better method for altering the dynamic range of pixel values in an image so that its intensity histogram has a desired shape. As we have seen, image enhancement by the contrast stretching operation is limited in the sense that it can apply only linear scaling functions.
Histogram processing techniques can be more powerful by employing non-linear (and non-monotonic) transfer functions to map the input pixel intensities to the output pixel intensities. In this section, we shall demonstrate the implementation of a couple of such techniques, namely histogram equalization and histogram matching, using the scikit-image library's exposure module. ...
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