Acta Optica Sinica, Volume. 38, Issue 2, 0210001(2018)
Adaptively-Weighted Blind Image Restoration Algorithm Based on Energy Constraint
An adaptively-weighted blind image restoration algorithm based on energy constraint is proposed. The images are divided into several sub-images and gradients of sub-images are introduced as weights to build the estimation model of weighted optical transfer function, which can reduce the influence of image texture on the estimation of optical transfer function. Based on the energy of image signals, the constraint equation is established, and the optimal restoration result is chosen by the dichotomy to realize adaptive blind image restoration. Results of simulation and multispectral remote sensing image experiments show that the proposed algorithm can produce high peak signal-to-noise ratio and structural similarity, which will effectively restore Gaussian blurred images, enhance the image resolution, and improve subjective visual effects. The proposed algorithm can be applied to the fields requiring large data and real-time monitoring.
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Chang Su, Tianjiao Fu, Xingxiang Zhang, Jianyue Ren, Longxu Jin. Adaptively-Weighted Blind Image Restoration Algorithm Based on Energy Constraint[J]. Acta Optica Sinica, 2018, 38(2): 0210001
Category: Image Processing
Received: Jul. 23, 2017
Accepted: --
Published Online: Aug. 30, 2018
The Author Email: Su Chang (suchang906@163.com)