Image Fusion based on Non-negative Matrix Factorization (MP-P5)

Author(s) : Junying Zhang (Electronics Engineering Institute, Xidian University, China) Le Wei (School of Computer Science, Xidian University, China) Qiguang Miao (Guilin Institute of Electronic Technology, China) Yue Wang (Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, USA)

Abstract : Non-negative Matrix Factorization technique (NMF) has been shown to have various applications to image processing, because of its power of local or part-based representation of objects and/or images. In this paper, we present an image fusion method based on NMF, not by the part-based representation feature of NMF, but by its wholly representation of the images needed to be fused: the images are fused by NMF with the parameter of the NMF to be set to 1. our experimental results show that the image fusion algorithm presented in this paper is efficient and effective compared with many other image fusion algorithms.

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