Journal ArticleDOI
Adaptive contrast enhancement and de-enhancement
Laxmikant Dash,B. N. Chatterji +1 more
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TLDR
Two different interpolative schemes for adaptive contrast enhancement have been presented for speeding up the contrast enhancement algorithm proposed by Beghdadi and Negrate and a contrast transformation function is proposed which can be used for adaptive enhancement as well as de-enhancement of images.About:
This article is published in Pattern Recognition.The article was published on 1991-02-20. It has received 59 citations till now. The article focuses on the topics: Contrast (vision).read more
Citations
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Journal ArticleDOI
A simple and effective histogram equalization approach to image enhancement
Heng-Da Cheng,Xiangjun Shi +1 more
TL;DR: The multi-peak generalized histogram equalization (multi-peak GHE) is proposed, which is improved by using multi- peak histogramequalization combined with local information to enhance the images effectively.
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A novel fuzzy logic approach to contrast enhancement
Heng-Da Cheng,Hui juan Xu +1 more
TL;DR: A novel adaptive direct fuzzy contrast enhancement method based on the fuzzy entropy principle and fuzzy set theory is proposed that is very effective in contrast enhancement as well as in preventing over-enhancement.
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A novel fuzzy logic approach to mammogram contrast enhancement
Heng-Da Cheng,Huijuan Xu +1 more
TL;DR: The experiments demonstrate that the proposed method can effectively enhance the contours and fine details of the mammographic features which will be useful for breast cancer diagnosis.
Journal ArticleDOI
Contrast enhancement based on a novel homogeneity measurement
Heng-Da Cheng,Mei Xue,X. J. Shi +2 more
TL;DR: A novel homogeneity measurement is proposed and utilize it to define and enhance the contrast and the results prove that the proposed method has better performance than the existing methods, no over-enhancement/under-enhancesment and more robust.
References
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Journal ArticleDOI
Adaptive histogram equalization and its variations
Stephen M. Pizer,Stephen M. Pizer,E. Philip Amburn,E. Philip Amburn,John D. Austin,Robert Cromartie,Ari Geselowitz,Ari Geselowitz,Trey Greer,Bart M. ter Haar Romeny,John B. Zimmerman,John B. Zimmerman +11 more
TL;DR: It is concluded that clipped ahe should become a method of choice in medical imaging and probably also in other areas of digital imaging, and that clip ahe can be made adequately fast to be routinely applied in the normal display sequence.
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Image processing in the context of a visual model
TL;DR: A specific relationship between some of the current knowledge and thought concerning human vision and the problem of controlling subjective distortion in processed images are reviewed.
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Image Enhancement by Histogram transformation
TL;DR: In this article, a number of simple and inexpensive enhancement techniques are suggested to make use of easily computed local context, features to aid in the reassignment of each point's gray level during histogram transfomation.
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Contrast enhancement technique based on local detection of edges
TL;DR: The technique, derived from Gordon's algorithm, accounts for visual perception criteria, namely for contour detection, and the efficiency of the algorithm is compared to Gordon's and to the classical ones.
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An evaluation of the effectiveness of adaptive histogram equalization for contrast enhancement
John B. Zimmerman,Stephen M. Pizer,Edward V. Staab,J. R. Perry,W. H. McCartney,B. C. Brenton +5 more
TL;DR: Results of these experiments show that for this particular diagnostic task, there was no significant difference in the ability of the two methods to depict luminance contrast; thus, further evaluation of AHE using controlled clinical trials is indicated.