Fuzzy intensification operator based contrast enhancement in the compressed domain
Applied Soft Computing
A histogram modification framework and its application for image contrast enhancement
IEEE Transactions on Image Processing
Context-based defading of archive photographs
Journal on Image and Video Processing - Special issue on image and video processing for cultural heritage
Morphological image enhancement procedure design by using genetic programming
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Human visual system for complexity reduction of image and video restoration
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part II
Optimal image restoration using HVS-based rate-distortion curves
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part II
Novel mean-shift based histogram equalization using textured regions
Expert Systems with Applications: An International Journal
Pattern Recognition and Image Analysis
Two-dimensional histogram equalization and contrast enhancement
Pattern Recognition
Fast image enhancement in compressed wavelet domain
Signal Processing
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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