吉林大学学报(工学版) ›› 2014, Vol. 44 ›› Issue (01): 225-234.doi: 10.13229/j.cnki.jdxbgxb201401037

• paper • Previous Articles     Next Articles

Adaptive image fusion based on image quality assessment parameter in NSST system

GAO Yin-han1, CHEN Guang-qiu2,3, LIU Yan-yan2,3   

  1. 1. State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China;
    2. College of Instrumentation & Electrical Engineering, Jilin University, Changchun 130061, China;
    3. School of Electronic and Information Engineering, Changchun University of Science and Technology, Changchun 130022, China
  • Received:2012-12-12 Online:2014-01-01 Published:2014-01-01

RICH HTML

0   

PDF (PC)

470

Abstract:

To enhance the multi-source image fusion accuracy, an adaptive fusion method based on image quality assessment parameter in Nonsubsampled Shearlet Transform (NSST) domain is proposed. The Source images are decomposed to subband images with multi-scale and multi-direction in NSST. The low frequency subband fusion rule is based on the structural similarity index with spatial frequency as coefficient weights. For the high frequency subands, the fusion rule of coefficient absolute value with neighborhood average energy consistency selection is adopted. The fused low and high frequency coefficients are reconstructed to image by nonsubsampled shearlet inverse transform. Fusion experiments are conducted with several sets of different modality images, and the objective assessment of fused results is done. The experiment results show that the proposed algorithm performs better in subjective and objective assessments than a few existing multi-scale fusion techniques, and obtains better fusion performance.

Key words: information processing, nonsubsampled shearlet transform, fusion rule, objective assessment, shift-invariant

CLC Number: 

  • TN911

[1] 胡钢, 刘哲, 徐小平, 等. 像素级图像融合技术的研究与进展[J].计算机应用研究, 2008, 25(3):650-655. Hu Gang, Liu Zhe, Xu Xiao-ping, et al. Research and recent development of image fusion at pixel level[J].Application Research of Computers, 2008, 25(3):650-655.

[2] Cheng Ying-lei, Zhao Rong-chun, Wang Bing, et al. An optimal algorithm of multisensor image fusion based on wavelet transform[C]//Processings of 7th International Conference on Signal Processing, Xi'an, 2004:1049-1051.

[3] Li Ming, Wu Shun-jun. A new image fusion algorithm based on wavelet transform[C]//Proceedings of 5th International Conference on Computational Intelligence and Multimedia Applications, Xi'an, 2003: 154-159.

[4] Candès E J, Donoho D L. New tight frames of curvelets and optimal representations of objects with piecewise C2 singularities[J]. Communications on Pure and Applied Mathematics, 2004, 57(2):219-266.

[5] Do M N, Vetterli M. The contourlet transform: an efficient directional multiresolution image representation[J]. IEEE Transactions on Image Processing, 2005, 14 (12):2091-2106.

[6] Easley G, Labate D, Lim W Q. Sparse directional image representations using the discrete shearlet transform[J].Applied and Computational Harmonic Analysis, 2008, 25(1):25-46.

[7] 叶传奇, 苗启广, 王保树. 基于非子采样的Contourlet变换的图像融合方法[J]. 计算机辅助设计与图形学学报, 2007, 19(10):1274-1278. Ye Chuan-qi, Miao Qi-guang, Wang Bao-shu. Image fusion method based on the nonsubsampled contourlet transform[J]. Journal of Computer-Aided Design & Computer Graphics, 2007, 19(10):1274-1278.

[8] Zheng You-zhi, Hou Xiao-dong, Bian Tian-tian, et al. Effective image fusion rules of multiscale image decomposition[C]//Proceedings of the 5th International Symposium on Image and Signal Processing and Analysis, Istanbul, 2007:362-366.

[9] 张强, 郭宝龙. 基于Curvelet变换的图像融合算法[J].吉林大学学报:工学版, 2007, 37(2):458-463. Zhang Qiang, Guo Bao-long. Image fusion algorithm using Curvelet transform[J].Journal of Jilin University (Engineering and Technology Edition), 2007, 37(2):458-463.

[10] Guo K, Labate D, Lim W Q, et al. Wavelets with composite dilations and their MRA properties[J]. Applied and Computational Harmonic Analysis, 2006, 20(2):202-236.

[11] Guo K, Labate D. Optimally sparse multidimensional representation using shearlets[J]. SIAM Journal on Mathematical Analysis, 2007, 39(1):298-318.

[12] Wang Zhou, Bovik Alan C, Sheikh Hamid R, et al. Image quality assessment: from error visibility to structural similarity[J]. IEEE Transactions on Image Processing, 2004, 13(4): 600-612.

[13] Eskicioglu A M, Fisher P S. Image quality measures and their performance[J]. IEEE Transactions on Communications, 1995, 43(12): 2959-2965.

[14] Leung L W, King B, Vohora V. Comparison of image data fusion techniques using entropy and INI[C]//Proc of 22nd Asian Conference on Remote Sensing, Singapore, 2001: 152-157.

[15] Qu Gui-hong, Zhang Da-li, Yan Ping-fan. Information measure for performance of image fusion[J]. Electronic Letters, 2002, 38(7):313-315.

[16] Xydeas C S, Petrovi V. Objective image fusion performance measure[J]. Electronics Letters, 2000, 36(4):308-309.

[17] Zhang Zhong, Blum Rick S. A categorization of multiscale decomposition-based image fusion schemes with a performance study for a digital camera application[J]. Proceedings of the IEEE, 1999, 87(8): 1315-1326.

[18] 王朝晖, 王佳琪, 赵德功, 等. 基于Shearlet与改进PCNN的图像融合[J].激光与红外, 2012, 42(2):213-216. Wang Zhao-hui, Wang Jia-qi, Zhao De-gong, et al.Image Fusion based on Shearlet and improved PCNN[J]. Laser & Infrared, 2012, 42(2):213-216.

[19] 叶传奇, 王宝树, 苗启广. 基于NSCT变换的红外与可见光图像融合算法[J].系统工程与电子技术, 2008, 30(4): 593-596. Ye Chuan-qi, Wang Bao-shu, Miao Qi-guang. Fusion algorithm of infrared and visible light images based on NSCT transform[J]. Systems Engineering and Electronics, 2008, 30(4):593-596.
[1] YING Huan,LIU Song-hua,TANG Bo-wen,HAN Li-fang,ZHOU Liang. Efficient deterministic replay technique based on adaptive release strategy [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1917-1924.
[2] LIU Zhong-min,WANG Yang,LI Zhan-ming,HU Wen-jin. Image segmentation algorithm based on SLIC and fast nearest neighbor region merging [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1931-1937.
[3] SHAN Ze-biao,LIU Xiao-song,SHI Hong-wei,WANG Chun-yang,SHI Yao-wu. DOA tracking algorithm using dynamic compressed sensing [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1938-1944.
[4] YAO Hai-yang, WANG Hai-yan, ZHANG Zhi-chen, SHEN Xiao-hong. Reverse-joint signal detection model with double Duffing oscillator [J]. 吉林大学学报(工学版), 2018, 48(4): 1282-1290.
[5] QUAN Wei, HAO Xiao-ming, SUN Ya-dong, BAI Bao-hua, WANG Yu-ting. Development of individual objective lens for head-mounted projective display based on optical system of actual human eye [J]. 吉林大学学报(工学版), 2018, 48(4): 1291-1297.
[6] CHEN Mian-shu, SU Yue, SANG Ai-jun, LI Pei-peng. Image classification methods based on space vector model [J]. 吉林大学学报(工学版), 2018, 48(3): 943-951.
[7] CHEN Tao, CUI Yue-han, GUO Li-min. Improved algorithm of multiple signal classification for single snapshot [J]. 吉林大学学报(工学版), 2018, 48(3): 952-956.
[8] MENG Guang-wei, LI Rong-jia, WANG Xin, ZHOU Li-ming, GU Shuai. Analysis of intensity factors of interface crack in piezoelectric bimaterials [J]. 吉林大学学报(工学版), 2018, 48(2): 500-506.
[9] LIN Jin-hua, WANG Yan-jie, SUN Hong-hai. Improved feature-adaptive subdivision for Catmull-Clark surface model [J]. 吉林大学学报(工学版), 2018, 48(2): 625-632.
[10] WANG Ke, LIU Fu, KANG Bing, HUO Tong-tong, ZHOU Qiu-zhan. Bionic hypocenter localization method inspired by sand scorpion in locating preys [J]. 吉林大学学报(工学版), 2018, 48(2): 633-639.
[11] YU Hua-nan, DU Yao, GUO Shu-xu. High-precision synchronous phasor measurement based on compressed sensing [J]. 吉林大学学报(工学版), 2018, 48(1): 312-318.
[12] WANG Fang-shi, WANG Jian, LI Bing, WANG Bo. Deep attribute learning based traffic sign detection [J]. 吉林大学学报(工学版), 2018, 48(1): 319-329.
[13] LIU Dong-liang, WANG Qiu-shuang. Instantaneous velocity extraction method on NGSLM data [J]. 吉林大学学报(工学版), 2018, 48(1): 330-335.
[14] TANG Kun, SHI Rong-hua. Detection of wireless sensor network failure area based on butterfly effect signal [J]. 吉林大学学报(工学版), 2017, 47(6): 1939-1948.
[15] LI Juan, MENG Ke-xin, LI Yue, LIU Hui-li. Seismic signal noise suppression based on similarity matched Wiener filtering [J]. 吉林大学学报(工学版), 2017, 47(6): 1964-1968.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright © Journal of Jilin University(Engineering and Technology Edition), All Rights Reserved.
Tel: +86-431-85095297　Fax: +86-431-85094074　E-mail: xbgxb@jlu.edu.cn
Powered by Beijing Magtech Co. Ltd