Transform Coefficient Histogram-Based Image Enhancement Algorithms Using Contrast Entropy

Many applications of histograms for the purposes of image processing are well known. However, applying this process to the transform domain by way of a transform coefficient histogram has not yet been fully explored. This paper proposes three methods of image enhancement: a) logarithmic transform hi...

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Vydáno v:IEEE transactions on image processing Ročník 16; číslo 3; s. 741 - 758
Hlavní autoři: Agaian, S.S., Silver, B., Panetta, K.A.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York, NY IEEE 01.03.2007
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:1057-7149, 1941-0042
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Shrnutí:Many applications of histograms for the purposes of image processing are well known. However, applying this process to the transform domain by way of a transform coefficient histogram has not yet been fully explored. This paper proposes three methods of image enhancement: a) logarithmic transform histogram matching, b) logarithmic transform histogram shifting, and c) logarithmic transform histogram shaping using Gaussian distributions. They are based on the properties of the logarithmic transform domain histogram and histogram equalization. The presented algorithms use the fact that the relationship between stimulus and perception is logarithmic and afford a marriage between enhancement qualities and computational efficiency. A human visual system-based quantitative measurement of image contrast improvement is also defined. This helps choose the best parameters and transform for each enhancement. A number of experimental results are presented to illustrate the performance of the proposed algorithms
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ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2006.888338