Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1784013 | Infrared Physics & Technology | 2016 | 9 Pages |
Abstract
Infrared images always suffer from blurring edges, fewer details and low signal-to-noise ratio. So, sharpening edges and suppressing noise become the urgent techniques in infrared image technology field. However, they are contradictories in most cases. Hence, to depict correctly infrared image features under low signal-to-noise ratio circumstance, a novel prior, which is immune to noise, is presented in this paper. The proposed method scopes noise suppression and details enhancement. In noise suppression, the prior is introduced into Bayesian model to obtain optimal estimation through iteration. In details enhancement, based on the proposed prior, the final image is obtained by the improved unsharp mask algorithm which enhances adaptively details and edges of optimal estimation. The effectiveness and robustness of the proposed method is analyzed by testing the infrared images obtained from different signal-to-noise ratio conditions. Compared with other well-established methods, the proposed method shows a significant performance in terms of noise suppression, actual scene reappearance, enhancing the details and sharpening edges.
Related Topics
Physical Sciences and Engineering
Physics and Astronomy
Atomic and Molecular Physics, and Optics
Authors
Zunlin Fan, Duyan Bi, Linyuan He, Shiping Ma,