A NEW ALGORITHM OF INFRARED IMAGE ENHANCEMENT BASED ON ROUGH SETS AND CURVELET TRANSFORM

被引：5
|
作者：
Tan, Jian-Hui [1 ,2 ]
Pan, Bao-Chang [1 ]
Liang, Jian [1 ]
Huang, Yong-Hui [1 ]
Fan, Xiao-Yan [1 ]
Pan, Jian-Jia [3 ]
机构：
[1] Guangdong Univ Technol, Fac Informat Engn, Guangzhou 510006, Guangdong, Peoples R China
[2] Yangjiang Vocat & Tech Coll, Dept Comp Sci, Yangjiang 529566, Peoples R China
[3] Hong Kong Baptist Univ, Dept Comp Sci, Hong Kong, Peoples R China
来源：
PROCEEDINGS OF 2009 INTERNATIONAL CONFERENCE ON WAVELET ANALYSIS AND PATTERN RECOGNITION | 2009年
关键词：
Rough sets; Curvelet transform; Infrared image; Image enhancement; Human visual properties;
D O I：
10.1109/ICWAPR.2009.5207419
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Infrared image enhancement is a research focus as well as one of the difficulties in the field of information processing. Rough sets theory is a new mathematical tool to solve the issue of ambiguity and uncertainty. Curvelet transform develops from wavelet transform and has noticeable effect in denoising and signal enhancing. Based on the features of infrared image and human visual properties and combined the rough sets theory and curvelet transform, this paper has put forward a new algorithm to enhance the weak infrared image. Based on human visual properties and noise conditional properties, this algorithm first partitions an infrared image into different sub-images in accordance with two properties: pixel gradient value and noise. Then enhance the sub-images via curvelet transforming. Experiments results have shown that this new algorithm can achieve good enhancing effect and can meet the actual needs of infrared image enhancement.
引用
收藏
页码：270 / +
页数：2
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