摘要
提出一种针对多重模糊图像的恢复算法,以解决航空成像中多重模糊同时作用时的图像恢复问题。对多重模糊的物理模型进行分析,通过分步去模糊对多重模糊图像进行恢复。对空间不变模糊的点扩散函数进行合并,减少多重模糊恢复过程的计算误差累计,通过一次解卷积运算实现多重空间不变模糊图像的恢复。对多重模糊图像在分步恢复过程中所产生的误差噪声进行分析,使用维纳滤波对阶段误差噪声进行抑制,使得恢复图像的峰值信噪比(PSNR)值提高7.76。实验结果表明基于点扩散函数合并的恢复方法能将多重模糊图像的PSNR值提高到28.09,有效地保障了图像的恢复质量。
An image restoration algorithm is proposed to restore the images simultaneously degraded by a multiple blur during aerial imaging. Based on the analysis of the physical model of the multiple blur, the multiple blur can be restored by deblurring the every sub-blur step by step. The Point Spread Functions （PSFs） of every space-invariant blur in the multiple blurred images are combined together by convolving all the linear PSFs to reduce the accumulation of calculation errors during the image restoration, so that the multiple blur made up of the space-invariant blurs can be eliminated by a deconvolution restoration. By analyzing the error noise caused by the image restoration, a Wiener filter is applied to suppress the error noise,which can increase the PSNR of the restored image by 7.76. The experiment results show that the PSNR of the image restored by the proposed algorithm based on the PSFs combination has reached 28.09, which ensures the acceptable restoration quality for aerial multiple blurred images.
出处
《光学精密工程》
EI
CAS
CSCD
北大核心
2009年第5期1161-1170,共10页
Optics and Precision Engineering
基金
国防科技预研基金资助项目(No.1040603)
