A New Point Spread Function Estimation Approach for Recovery of Atmospheric Turbulence Degraded Photographs
Images acquired by an optical system are usually degraded by atmospheric turbulence, which exists in the path between the targets and the imaging system. The estimation of atmospheric turbulence degraded Point Spread Function (PSF) without any prior knowledge of clear images is the most challenging and significant technique on image restoration. In this paper, a new PSF estimation approach is proposed for long-exposure atmospheric turbulence degraded images, and is applied to image restoration successfully. The PSF is estimated via an isosceles model which is proposed to approximate one component of the original images Fourier amplitude. On degraded image restoration, the short-exposure image frames are transformed into a single long-exposure image, and then the restored image is obtained by using the estimated PSF and Wiener Filter. Numerical experiments suggest that this algorithm can obtain accurate PSF from both synthetic and real images. It is also shown objectively that the quality of restored images is greatly enhanced, by applying the Gray Mean Grads and Laplacian Sum standards.
atmospheric turbulence long-exposure PSF estimation image restoration
Hong ZHANG Qi GE Lu LI Yuecheng LI Kaiyu XI
Image Processing Centre Beihang University, 100191 Beijing, China
国际会议
2011 4th International Congress on Image and Signal Processing(第四届图像与信号处理国际学术会议 CISP 2011)
上海
英文
789-793
2011-10-15（万方平台首次上网日期，不代表论文的发表时间）