Clustering with Multi-Viewpoint based Similarity Measure
Keywords:
Histogram equalization ,gray scale ,global histogram equalization Gaussian mixture model, Mean Preserving Bi-histogram Equalization, Dualistic Subimage Histogram Equalization, Minimum Mean Brightness Error Bi-histogram Equalization, Recursive Mean-Separate Histogram EqualizationAbstract
In this paper, we have optimized the the various histogram equalization algorithm for image contrast enhancement Histogram equalization (HE), the representative method for contrast enhancement, has been developed to satisfy humans with its resultant images. This technique is widely used because it is simple and easy to invoke. This can be used for contrast enhancement of all types of images, The classic histogram equalization provides to best visual performance in certain level compare to the other histogram equalization techniques, but has this method does not preserve the actual brightness and actual appearance of the image
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Published
2014-07-14
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Articles
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
How to Cite
[1]
“Clustering with Multi-Viewpoint based Similarity Measure”, IEJRD - International Multidisciplinary Journal, vol. 1, no. 2, p. 5, Jul. 2014, Accessed: Sep. 30, 2026. [Online]. Available: https://www.iejrd.com/index.php/iejrd/article/view/160
