DSA image fusion based on dynamic fuzzy logic and curvelet entropy

作     者：Zhang, Guangming Cui, Zhiming Li, Fanzhang Wu, Jian 

作者机构：The Institute of Intelligent Information Processing and Application Soochow University Suzhou 215006 China 

出 版 物：《Journal of Multimedia》 (J. Multimedia)

年 卷 期：2009年第4卷第3期

页      面：129-136页

核心收录：

学科分类：0831[工学-生物医学工程（可授工学、理学、医学学位）] 0710[理学-生物学] 08[工学] 0835[工学-软件工程] 0836[工学-生物工程] 0803[工学-光学工程] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Image fusion 

摘      要：The curvelet transform as a multiscale transform has directional parameters occurs at all scales, locations, and orientations. It is superior to wavelet transform in image processing domain. This paper analyzes the characters of DSA medical image, and proposes a novel approach for DSA medical image fusion, which is using curvelet information entropy and dynamic fuzzy logic. Firstly, the image was decomposed by curvelet transform to obtain the different level information. Then the entropy from different level of DSA medical image was calculated, and a membership function based on dynamic fuzzy logic was constructed to adjust the weight for image subbands coefficients via entropy. At last an inverse curvelet transform was applied to reconstruct the image to synthesize one DSA medical image which could contain more integrated accurate detail information of blood vessels than any one of the individual source images. By compare, the efficiency of our method is better than weighted average, laplacian pyramid and traditional wavelet transform method. © 2009 ACADEMY PUBLISHER.