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Adaptive and integrated neighborhood-dependent approach for nonlinear enhancement of color images

[+] Author Affiliations
Li Tao

Old Dominion University, Department of Electrical and Computer Engineering, Computational Intelligence and Machine Vision Laboratory, Norfolk, Virginia 23529

Vijayan K. Asari

Old Dominion University, Department of Electrical and Computer Engineering, Computational Intelligence and Machine Vision Laboratory, Norfolk, Virginia 23529

J. Electron. Imaging. 14(4), 043006 (December 12, 2005). doi:10.1117/1.2136903
History: Received June 15, 2004; Revised April 07, 2005; Accepted April 28, 2005; Published December 12, 2005; Online December 12, 2005
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A novel image enhancement algorithm called AINDANE (adaptive and integrated neighborhood dependent approach for nonlinear enhancement) for improving the visual quality of digital images captured under extremely low or nonuniform lighting conditions is proposed. AINDANE is comprised of two separate processes, namely, adaptive luminance enhancement and adaptive contrast enhancement, to provide more flexibility and better control over image enhancement. Adaptive luminance enhancement is a global intensity transformation based on a specifically designed nonlinear transfer function, which is self-tuned by the histogram statistics of the input image. This process largely increases the luminance of darker pixels and compresses the dynamic range of the image at the same time. Adaptive contrast enhancement tunes the intensity of each pixel based on its relative magnitude with respect to the neighboring pixels. This process is also adaptively controlled by the global statistics of the image. A color restoration process, based on the relationship between the spectral bands and the luminance of the original image, is applied to convert the enhanced intensity image back to a color image.

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© 2005 SPIE and IS&T

Citation

Li Tao and Vijayan K. Asari
"Adaptive and integrated neighborhood-dependent approach for nonlinear enhancement of color images", J. Electron. Imaging. 14(4), 043006 (December 12, 2005). ; http://dx.doi.org/10.1117/1.2136903


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