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OpenCV Computer Vision Application Programming Cookbook Second Edition

OpenCV Computer Vision Application Programming Cookbook Second Edition

By : Robert Laganiere
3.7 (3)
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OpenCV Computer Vision Application Programming Cookbook Second Edition

OpenCV Computer Vision Application Programming Cookbook Second Edition

3.7 (3)
By: Robert Laganiere

Overview of this book

OpenCV 3 Computer Vision Application Programming Cookbook is appropriate for novice C++ programmers who want to learn how to use the OpenCV library to build computer vision applications. It is also suitable for professional software developers wishing to be introduced to the concepts of computer vision programming. It can also be used as a companion book in a university-level computer vision courses. It constitutes an excellent reference for graduate students and researchers in image processing and computer vision.
Table of Contents (13 chapters)
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12
Index

Equalizing the image histogram


In the previous recipe, we showed you how the contrast of an image can be improved by stretching a histogram so that it occupies the full range of the available intensity values. This strategy indeed constitutes an easy fix that can effectively improve an image. However, in many cases, the visual deficiency of an image is not that it uses a too-narrow range of intensities. Rather, it is that some intensity values are used more frequently than others. The histogram shown in the first recipe of this chapter is a good example of this phenomenon. The middle-gray intensities are indeed heavily represented, while darker and brighter pixel values are rather rare. In fact, you would think that a good-quality image should make equal use of all available pixel intensities. This is the idea behind the concept of histogram equalization, that is, making the image histogram as flat as possible.

How to do it...

OpenCV offers an easy-to-use function that performs histogram equalization...

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