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
相关论文
共 50 条
  • [1] The Fuzzy Nonlinear Enhancement Algorithm of Infrared Image Based on Curvelet Transform
    Zhao, Jingchao
    Qu, Shiru
    CEIS 2011, 2011, 15
  • [2] A new image fusion algorithm based on curvelet transform
    Institute of Optoelectronic Engineering, Jinan University, Guangzhou 510632, China
    Guangdianzi Jiguang, 2008, 7 (963-966): : 963 - 966
  • [3] Automatic SAR Image Enhancement Based on Curvelet Transform and Genetic Algorithm
    Hu, Jie
    Li, Ying
    Jia, Yu
    INTELLIGENT SCIENCE AND INTELLIGENT DATA ENGINEERING, ISCIDE 2011, 2012, 7202 : 326 - 333
  • [4] MRI Image Enhancement Algorithm Based on the Second Generation Curvelet Transform
    Wang, Da-xi
    Chen, Xin-xin
    INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER SCIENCE AND ENGINEERING (ACSE 2014), 2014, : 125 - 129
  • [5] A new adaptive algorithm for image denoising based on curvelet transform
    Chen, Musheng
    Cai, Zhishan
    MIPPR 2013: REMOTE SENSING IMAGE PROCESSING, GEOGRAPHIC INFORMATION SYSTEMS, AND OTHER APPLICATIONS, 2013, 8921
  • [6] Image Resolution Enhancement based on Curvelet Transform
    Haddad, Zehira
    Tong, Adrien Chan Hon
    Krahe, Jaime Lopez
    PROCEEDINGS OF THE 12TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (VISIGRAPP 2017), VOL 4, 2017, : 167 - 173
  • [7] Algorithm for image fusion based on curvelet transform
    Xu, Xing
    Li, Ying
    Sun, Jinqiu
    Zhang, Yanning
    Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University, 2008, 26 (03): : 395 - 398
  • [8] An image BSS algorithm based on curvelet transform
    Wang, Junhua
    2008 INTERNATIONAL CONFERENCE ON AUDIO, LANGUAGE AND IMAGE PROCESSING, VOLS 1 AND 2, PROCEEDINGS, 2008, : 1035 - 1039
  • [9] Visible and Infrared Image Fusion Based on Curvelet Transform
    Quan, Siji
    Qian, Weiping
    Guo, Junhai
    Zhao, Hua
    2014 2ND INTERNATIONAL CONFERENCE ON SYSTEMS AND INFORMATICS (ICSAI), 2014, : 828 - 832
  • [10] An Improved infrared and visible image fusion algorithm based on the Second Generation Curvelet Transform
    Liu Xiaojun
    Wang Jianyu
    PROCEEDINGS OF THE 2014 INTERNATIONAL CONFERENCE ON MECHATRONICS, CONTROL AND ELECTRONIC ENGINEERING, 2014, 113 : 281 - 284
12345