MULTI-FOCUS IMAGE FUSION ALGORITHM BASED ON NSCT

被引:0
作者
Yan, Yahao [1 ]
Du, Junping [1 ]
Li, Qingping [1 ]
Zuo, Min [2 ]
Lee, JangMyung [3 ]
机构
[1] Beijing Univ Posts & Telecommun, Sch Comp Sci, Beijing Key Lab Intelligent Telecommun Software, Beijing 100876, Peoples R China
[2] Beijing Technol & Business Univ, Sch Comp & Informat Engn, Beijing 100048, Peoples R China
[3] Pusan Natl Univ, Dept Elect Engn, Busan, South Korea
来源
2012 IEEE 2ND INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND INTELLIGENT SYSTEMS (CCIS) VOLS 1-3 | 2012年
基金
北京市自然科学基金; 中国国家自然科学基金;
关键词
Image fusion; NSCT transform; Box-counting dimension; Local space frequency;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper is aimed at the problem of Multifocus image fusion for the same scene and has proposed a multi-focus image fusion algorithm based on NSCT [1] (The Nonsubsampled Contourlet Transform). NSCT is the sparse representation of a two-dimension piecewise smooth signals, not only satisfying the anisotropic scaling relation and having the multi-scale, multi-directional characteristics, and shift invariance, but also being able to accurately capture the image information of the contour feature and texture details. In proposed algorithm, NSCT transform is first used to decompose source images at each scale and direction to get low-pass sub-band coefficients and band-pass directional sub-band coefficients. Then, the fusion rule of weighted box-counting dimension is adopted in low-pass sub-band, as well as the fusion rule of local space frequency in band-pass directional sub-band. Finally, the NSCT inverse transform is employed to get the fused image. Through check experiment, our algorithm is proved to be simple and effective.
引用
收藏
页码:85 / 89
页数:5
相关论文
共 12 条
[1]   The nonsubsampled contourlet transform: Theory, design, and applications [J].
da Cunha, Arthur L. ;
Zhou, Jianping ;
Do, Minh N. .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2006, 15 (10) :3089-3101
[2]   The contourlet transform: An efficient directional multiresolution image representation [J].
Do, MN ;
Vetterli, M .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2005, 14 (12) :2091-2106
[3]   Image Quality Assessment Based on Multiscale Geometric Analysis [J].
Gao, Xinbo ;
Lu, Wen ;
Tao, Dacheng ;
Li, Xuelong .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2009, 18 (07) :1409-1423
[4]  
Jia Jian, 2007, Acta Electronica Sinica, V35, P1934
[5]   Hybrid Multiresolution Method for Multisensor Multimodal Image Fusion [J].
Li, Shutao ;
Yang, Bin .
IEEE SENSORS JOURNAL, 2010, 10 (09) :1519-1526
[6]   Biological image fusion using a NSCT based variable-weight method [J].
Li, Tianjie ;
Wang, Yuanyuan .
INFORMATION FUSION, 2011, 12 (02) :85-92
[7]  
[梁东方 Liang Dongfang], 2002, [中国图象图形学报. A, Journal of image and graphics], V7, P246
[8]   Image Fusion Technique using Multi-resolution Singular Value Decomposition [J].
Naidu, V. P. S. .
DEFENCE SCIENCE JOURNAL, 2011, 61 (05) :479-484
[9]   Optimal sensor rules and unified fusion rules for multisensor multi-hypothesis network decision systems with channel errors [J].
Ren, Qing'an ;
Zhu, Yunmin ;
Shen, Xiaojing ;
Song, Enbin .
AUTOMATICA, 2009, 45 (07) :1694-1702
[10]   A case study with design of experiments: Performance evaluation methodology for Level 1 distributed data fusion processes [J].
Sambhoos, Kedar ;
Bowman, Christopher ;
Llinas, James .
INFORMATION FUSION, 2011, 12 (02) :93-104