Journal of Jilin University Science Edition ›› 2020, Vol. 58 ›› Issue (4): 931-936.
Previous Articles Next Articles
ZHU Hongwei
Received:
Online:
Published:
Contact:
Abstract: Aiming at the problem that singlemodality medical images could not provide comprehensive and complementary information for clinical diagnosis, the author proposed a multimodal medical image fusion method based on nonsubsampled shearlet transform (NSST) and improved sparse representation (ISR). Firstly, the NSST tool was used to decompose the source image into a low frequency subband and several high frequency subbands. Secondly, the ISR method was used to fuse the lowfrequency subbands, and the details of the lowfrequency subbands were removed by the sobel operator and the guided filter, thereby improving the fusion efficiency of the lowfrequency subbands. At the same time, the highfrequency subbands were fused by using the maximum absolute value fusion rule. Finally, the final fused image was obtained by the inverse NSST transform of the fused lowfrequency and highfrequency subbands. Experimental results show that proposed method is superior to other fusion methods in subjective visual performance and objective evaluation.
Key words: medical image fusion, nonsubsampled shearlet, improved sparse representation, fusion rule
CLC Number:
ZHU Hongwei. Medical Image Fusion Method Based on NSST and Improved Sparse Representation[J].Journal of Jilin University Science Edition, 2020, 58(4): 931-936.
0 / / Recommend
Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks
URL: http://xuebao.jlu.edu.cn/lxb/EN/
http://xuebao.jlu.edu.cn/lxb/EN/Y2020/V58/I4/931
Cited