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Comparative study of logarithmic image processing models for medical image enhancement
Zhao Z.; Zhou Y.
2017-02-06
Conference NameIEEE International Conference on Systems, Man, and Cybernetics (SMC)
Source Publication2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings
Pages1046-1050
Conference DateOCT 09-12, 2016
Conference PlaceBudapest, HUNGARY
Abstract

Medical image enhancement is an effective tool to improve visual quality of digital medical images. However, conventional linear image enhancement methods often suffers from problems such as over-enhancement and noise sensitivity. In this paper, we study nonlinear arithmetic frameworks designed to solve the common problems of linear enhancement methods, namely, LIP, PLIP and GLIP. We also introduce nonlinear unsharp masking algorithms based on the logarithmic image processing models for medical image enhancement. Experiments are conducted to evaluate and compare the performance of the methods.

KeywordGeneralized Logarithmic Image Processing Logarithmic Image Processing Medical Image Enhancement Parameterized Logarithmic Image Processing Unsharp Masking
DOIhttp://doi.org/10.1109/SMC.2016.7844380
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Cybernetics ; Computer Science, Information Systems
WOS IDWOS:000402634701001
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Cited Times [WOS]:1   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionFaculty of Science and Technology
DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
AffiliationUniversidade de Macau
Recommended Citation
GB/T 7714
Zhao Z.,Zhou Y.. Comparative study of logarithmic image processing models for medical image enhancement[C],2017:1046-1050.
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