Research and Simulation of Image Histogram Matching

Wei Ping Zhao; Jun Yang; Yu Feng Li

doi:10.4028/www.scientific.net/AMR.748.659

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 748Research and Simulation of Image Histogram...

Research and Simulation of Image Histogram Matching

Abstract:

This article according to the characteristics of the image enhancement and the histogram of the image properties, using genetic algorithms to improve the image gray-scale. Optimization process is to optimize the shape parameters of a normalized to unit interval doublet Gaussian function. The simulation results show that: the purpose of the image enhancement is pull the distance between object and image in gray-scale coordinates, proving the effectiveness of the methods. Lay the foundation for the binary image and target feature extraction.

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Periodical:

Advanced Materials Research (Volume 748)

Pages:

659-662

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.748.659

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Online since:

August 2013

Authors:

Wei Ping Zhao, Jun Yang, Yu Feng Li

Keywords:

Bimodal Gaussian Function, Genetic Algorithm (GA), Histogram Matching, Image Enhancement

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References

[1] Rafael C. Gonzalez, Richard E. Woods,Digital Image Processing Second Edition,[M].Beijing, Publishing House of Electronics Industry,2006: 88–103, March.

Google Scholar

[2] Randy L. Haupt, Sue Ellen Haupt, Practical Genetic Algorithms, second ed. [M], vol. 2. Pennsylvania: Wiley-Interscience, 2004:102–110.

Google Scholar

[3] Mark S.Nixon, Alberto S.Aguado, Feature Extraction and Image Processing Second Edition, [M]. Beijing,Publishing House of Electronics Industry: 2011: 271–350.

Google Scholar

[4] Sikora,T.[1997].mpga Digital Video-Coding Standards.IEEE Signal Processing, vol. 14,no.5, pp.82-99.

Google Scholar

[5] Milan Sonka, Vaclav Hlavac, Image Processing,Analysis,and Machine Vision,Third Edition, [M]. Beijing, Tsinghua University Press. 2011: 88–120.

Google Scholar

[6] Basart J.P.,and Gonzalez R.C.[1992]. Binary Morphology, in Advances in Image Analysis, Y.Mahdavieh and R.C. Gonzalez(eds.),SPIE Press, Bellingham,wash.,pp.277-305.

Google Scholar

[7] Bisignani, W, T. Richards, G. P., and Whelan, J. W. [1996].The Improved Grey Scale and Coarse-Fine PCM Systems: Two New Digital TV Bandwith Reduction Techniques. " Proc.IEEE,vol.54,no.3,pp.376-390.

DOI: 10.1109/proc.1966.4699

Google Scholar

[8] Blahut, R.E. [1987].Principles and Practice of Information Theory,Addison-Wesley,Reading, Mass.

Google Scholar