An Entropy Interpretation of the Logarithmic Image Processing Model With Application to Contrast Enhancement

The logarithmic image processing (LIP) model is a mathematical theory that provides new operations for image processing. The contrast definition has been shown to be consistent with some important physical laws and characteristics of human visual system. In this paper, we establish an information-th...

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Bibliographic Details
Published in:	IEEE transactions on image processing Vol. 18; no. 5; pp. 1135 - 1140
Main Author:	Deng, Guang
Format:	Journal Article
Language:	English
Published:	New York, NY IEEE 01.05.2009 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Adaptive algorithms Applied sciences Biological system modeling Detection, estimation, filtering, equalization, prediction Entropy Exact sciences and technology Filters Gray-scale Human Humans Image contrast Image enhancement Image processing information content Information theory Information, signal and communications theory logarithmic image processing (LIP) model Mathematical model Mathematical models Noise reduction relative entropy Signal and communications theory Signal processing Signal, noise Telecommunications and information theory Visual Visual system Image quality Adaptive algorithm Logarithmic function Image processing information content relative entropy Entropy logarithmic image processing (LIP) model Image enhancement Noisy image Information interpretation Information theory
ISSN:	1057-7149, 1941-0042
Online Access:	Get full text
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