基于低秩稀疏分解的湍流退化图像序列的盲去卷积算法

针对湍流退化图像序列存在像偏移、像抖动和像 模糊的问题,提出一种基于低秩稀疏分解和多帧去 卷积的图像复原算法。首先分析大气湍流下图像序列的退化特征,然后在低秩稀疏分解的思 想下,采用非增广拉格朗日乘子(IALM)法优化由低秩 矩阵的核范数和稀疏 矩阵的Frobenius范数之和构成的目标函数,将湍流退化序列分解为低秩稳像和稀疏湍流两 部分；最后利用 多帧去卷积算法复原对齐的稳像。实验结果表明,本文算法能够有效校 正湍流像素偏移,在提高复原质量和速度方面取得了明显的效果。

A multi-frame blind deconvolution algorithm based on low-rank decomposition for turbulence-degraded images

In order to correct pixel distortion and reduce time-varying blur,a novel blind restoration algorithm based on low-rank decomposition is proposed in this paper,which is capable of r estoring a high-quality image from the turbulence-degraded image sequence.The paper firstly analyzes the infrared imag e characteristics at the atmospheric turbulence.Next,it decomposes the turbulence sequence into two comp onents of the stabilized background,the turbulence and noise through low-rank decomposition.The decom position is simplified into a minimization of nuclear norm and Frobenius norm,optimized by inexact augmented Lagrange multiplier (IALM).Finally, a multi-frame blind deconvolution algorithm is implemented to deblur the stabil ized images,generating the final output.Experimental results verify the effectiveness of the algorithm.I t can effectively alleviate blur and distortions,improve visual quality and recovery speed significantly.