Volume 36, Number 1, February 2018
|Page(s)||103 - 109|
|Published online||18 May 2018|
Dark Channel Constraint and Alternated Direction Multiplier Optimization of Turbulence Degraded Image Blind Restoration
School of Automation, Northwestern Polytechnical University, Xi'an 710129, China
2 Xi'an Satellite Control Center, Xi'an 710043, China
In order to improve the effect of turbulence degraded image restoration, aiming at the problem that the fuzzy solution is easy to be obtained by using the prior information constraint of gradient distribution under the framework of maximum a posteriori probability of blind restoration algorithm, this paper proposes a dark channel constraint and alternated direction multiplier optimization of turbulence degraded image blind restoration method.First, based on the idea of multi-scale, a dark channel prior constraint is imposed on the image and non-negative constraints and energy constraints are imposed on the point spread function at each level.Then, the kernel and image of the current scale are estimated by alternating iterations of coordinate descent method. When the maximum scale is reached, the final estimated blur kernel is obtained.Last, combined with the total variational model, the image details are quickly restored using the alternate direction optimization method. The experimental results show that the prior information constraint used in the proposed algorithm is advantageous to obtain a clear solution, and can converge to the global optimal solution in the total variational model, which can effectively suppress the artifacts produced in the image restoration process and recover a better target image detail.
Key words: image processing / turbulence image blind restoration / dark channel constraint / alternated direction optimization methods / deconvolution / total variational / point spread function
关键字 : 图像处理 / 湍流图像盲复原 / 暗通道约束 / 交替方向乘子法优化 / 反卷积 / 总变分 / 点扩散函数
© 2018 Journal of Northwestern Polytechnical University. All rights reserved.
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