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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Vydané v:	IEEE transactions on image processing Ročník 16; číslo 3; s. 741 - 758
Hlavní autori:	Agaian, S.S., Silver, B., Panetta, K.A.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York, NY IEEE 01.03.2007 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Applied sciences Artificial intelligence Coefficients Computational efficiency Computer Graphics Computer science; control theory; systems Computer Simulation Contrast entropy contrast measure Detection, estimation, filtering, equalization, prediction discrete cosine transform (DCT) Discrete cosine transforms discrete Fourier transform (DFT) Discrete Fourier transforms Discrete transforms Entropy Exact sciences and technology Fast Fourier transforms Fourier transforms Histograms human vision system Humans Image enhancement Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image processing Information Storage and Retrieval - methods Information, signal and communications theory Miscellaneous Models, Statistical Numerical Analysis, Computer-Assisted Pattern recognition. Digital image processing. Computational geometry Reproducibility of Results Sensitivity and Specificity Signal and communications theory Signal processing Signal, noise Silver Telecommunications and information theory transform histogram Transforms Performance evaluation Computer vision Histogram transform histogram Logarithmic function Image processing Discrete Fourier transformation Gaussian distribution discrete Fourier transform (DFT) Entropy Vision system Equalization Algorithm discrete cosine transform (DCT) Image method Optimization contrast measure Image quality Contrast entropy Signal processing human vision system Discrete cosine transforms Image enhancement Image contrast
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
Bibliografia:	ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Undefined-1 ObjectType-Feature-3 content type line 23
ISSN:	1057-7149 1941-0042
DOI:	10.1109/TIP.2006.888338