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Multi-frame blind deconvolution of atmospheric turbulence degraded images with mixed noise models

机译:具有混合噪声模型的大气湍流退化图像的多帧盲反卷积

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摘要

This paper proposes a mixed noise model and uses the multi-frame blind deconvolution to restore the images of space objects under the Bayesian inference framework. To minimize the cost function, an algorithm based on iterative recursion was proposed. In addition, three limited bandwidth constraints of the point spread functions were imposed into the solution process to avoid converging to local minima. Experimental results show that the proposed algorithm can effectively restore the turbulence degraded images and alleviate the distortion caused by the noise.
机译:本文提出了一种混合噪声模型,并在贝叶斯推理框架下使用多帧盲反卷积来还原空间物体的图像。为了最小化代价函数,提出了一种基于迭代递归的算法。另外,点扩展函数的三个有限带宽约束被强加到求解过程中,以避免收敛到局部最小值。实验结果表明,该算法可以有效地还原湍流退化图像,减轻噪声引起的失真。

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