Image Fusion with Sparse Representation

Abstract:

Sparse representation is a new image representation theory. It can accurately represent the image information. In this paper, a novel fusion scheme using sparse representation is proposed. The sparse representation is conducted on overlapping patches. Each source image is divided into patches, and all the patches are transformed into vectors. Decompose the vectors into theirs sparse representations using orthogonal matching pursuit. Sparse coefficients are fused with the maximum absolute. The simulation results show that the proposed method can provide high-quality images.

• Periodical: Advanced Materials Research (Volumes 798-799)
• Pages: 737-740
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.798-799.737
• Online since: September 2013
• Authors: Hong Li, Jin Ping Zhang, Fen Xia Wu, Cong E Tan
• Keywords: Image Fusion, Orthogonal Matching Pursuit, Sparse Representation

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