Joint Exact Histogram Specification and Image Enhancement Through the Wavelet Transform

Histogram specification (equalization) is an important tool for tasks such as image enhancement and normalization. Although this problem has exact solution for continuous images, in the case of digital images, it is ill posed. Recently, an exact pixel ordering method based solely on local image inte...

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Bibliographic Details
Published in:IEEE transactions on image processing 2007-09, Vol.16 (9), p.2245-2250
Main Authors: Wan, Yi, Shi, Dongbin
Format: Article
Language:English
Subjects:
Algorithms
Computer Graphics
Computer Simulation
Continuous wavelet transforms
Data Interpretation, Statistical
Digital images
Gray-scale
Histogram specification (HS)
Histograms
Image enhancement
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Mathematical models
Models, Statistical
normalization
Numerical Analysis, Computer-Assisted
Order disorder
Performance enhancement
Pixel
pixel ordering
Pixels
Reproducibility of Results
Sensitivity and Specificity
Signal Processing, Computer-Assisted
Specifications
Watermarking
Wavelet coefficients
wavelet transform
Wavelet transforms
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Summary:Histogram specification (equalization) is an important tool for tasks such as image enhancement and normalization. Although this problem has exact solution for continuous images, in the case of digital images, it is ill posed. Recently, an exact pixel ordering method based solely on local image intensity was proposed, yet still with some limitations, especially since it ignores the important image edge information. In this paper, we present a wavelet-based method that simultaneously achieves the exact histogram specification and good image enhancement performance. It does so through a carefully designed strict pixel ordering process, during which the wavelet coefficients are fine tuned for the image enhancement purpose. Compared to previous work, this approach takes into account not only local mean intensity values, but also local edge information. Other advantages include fast pixel ordering, good statistical models, and better image enhancement performance. Experimental results and comparison with state-of-the-art methods are presented.
ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2007.902332