@inproceedings{692d695d4df54920ab743e41ce83824b,
title = "A novel image fusion algorithm based on structural similarity",
abstract = "In this paper, we propose an improved image fusion algorithm, which uses structural similarity to match the local energy of images. The local energy method can reflect the complemen-tarity between different types of images. But for grayscale images and infrared images which have very different intensity, the fusion between them can produce dark spots in the result. To avoid this, we introduce a structural similarity model. We also improve the low and high frequency fusion rules to avoid the loss of low frequency information and keep the edge information in the image. We did experiments in Matlab and the results show that our method out-perform the traditional methods with respect to entropy, average gradient and spatial frequency.",
keywords = "Image fusion, Infrared image, Local energy, Structural similarity, Visible light image",
author = "Yuan Zhou and Su, \{Zhen Qiang\} and Yang, \{Xin Yu\}",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2nd International Conference on Multimedia and Image Processing, ICMIP 2017 ; Conference date: 17-03-2017 Through 19-03-2017",
year = "2017",
month = dec,
day = "15",
doi = "10.1109/ICMIP.2017.63",
language = "英语",
series = "Proceedings - 2017 2nd International Conference on Multimedia and Image Processing, ICMIP 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "128--135",
booktitle = "Proceedings - 2017 2nd International Conference on Multimedia and Image Processing, ICMIP 2017",
}