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A Generalized Contrast Enhancement Method for Greyscale and Colored Images

Archana Chaudhari Published in Image Processing

CAE Proceedings on International Conference on Communication Technology
Year of Publication: 2016
© 2015 by CAE Journal

Archana Chaudhari. Article: A Generalized Contrast Enhancement Method for Greyscale and Colored Images. CAE Proceedings on International Conference on Communication Technology ICCT 2015(2):7-13, February 2016. Published by Foundation of Computer Science, New York, USA. BibTeX

@article{key:article,
	author = {Archana Chaudhari},
	title = {Article: A Generalized Contrast Enhancement Method for Greyscale and Colored Images},
	journal = {CAE Proceedings on International Conference on Communication Technology},
	year = {2016},
	volume = {ICCT 2015},
	number = {2},
	pages = {7-13},
	month = {February},
	note = {Published by Foundation of Computer Science, New York, USA}
}

Abstract

Image contrast enhancement techniques can be used in various image processing applications. There are various Image contrast enhancement techniques available. It depends on the particular type of image, which technique will prove better. Histogram equalization is one of the best technique that can be used for contrast enhancement. Different variants of Histogram equalization like Adaptive Histogram Equalization, Contrast Limited Adaptive Histogram equalization, Multiscale Adaptive Histogram Equalization, Dynamic Histogram Equalization, Partially overlapped sub-block Histogram Equalization, etc. can also be used. All these techniques mentioned proves good for a particular type of image, but they are not generalized methods which can be used for broad variety of images. A new method of contrast enhancement called as Gray level grouping (GLG) is suggested in this paper. GLG is a generalized method and can be used satisfactorily for broad variety of images. A variant of GLG, i. e. Adaptive Gray Level grouping (AGLG) is also discussed. [4]

References

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Keywords

Gray level grouping (GLG), AHE, MAHE, CLAHE, DHE, POSHE, low contrast images, bins.