Comparative Study of Logarithmic Image Processing Models for Medical Image Enhancement

被引：0
|
作者：
Zhao, Zhou [1 ]
Zhou, Yicong [1 ]
机构：
[1] Univ Macau, Dept Comp & Informat Sci, Macau, Peoples R China
来源：
2016 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC) | 2016年
关键词：
medical image enhancement; unsharp masking; logarithmic image processing; parameterized logarithmic image processing; generalized logarithmic image processing;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
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页码：1046 / 1050
页数：5
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