1. Image Fusion with Sparse Representation
- Author
-
Cong E Tan, Fen Xia Wu, Hong Li, and Jin Ping Zhang
- Subjects
Fusion scheme ,Image fusion ,K-SVD ,business.industry ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,General Engineering ,Pattern recognition ,Sparse approximation ,Matching pursuit ,Image (mathematics) ,Image representation ,Source image ,Computer vision ,Artificial intelligence ,business ,Mathematics - 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.
- Published
- 2013