Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6938461 | Journal of Visual Communication and Image Representation | 2016 | 15 Pages |
Abstract
This paper proposes an image fusion method based on an improved Stagewise OMP algorithm (ApStOMP), which is more efficient than StOMP in finding the sparest solution of large-scale underdetermined problem. Multiple atoms can be selected at each stage, and only a fixed number of stages are required. Unlike StOMP, we restrict the mutual coherence of selected atoms to be as low as possible at each stage, and atoms with high coherence are excluded. In this way, we can obtain a more accurate estimated support set than with StOMP. The advantages of the proposed fusion method are demonstrated experimentally with different groups of pre-registered source images, for which we can carry out image denoising and fusion simultaneously. The experimental results show that the performance of the proposed method is competitive with other methods in terms of several objective fusion metrics, as well as in visual quality.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Bin Liao, Lei Yan, Wei Mo, Jing Shen, Wenyao Zhang,