Multiframe blind deconvolution of atmospheric turbulence-degraded images based on filter

2007 ◽  
Author(s):  
Jianming Huang ◽  
Mangzuo Shen ◽  
Qiang Li
Keyword(s):  
Atmospheric Turbulence ◽  
Blind Deconvolution ◽  
Degraded Images

scholarly journals Multi‐frame blind deconvolution of atmospheric turbulence degraded images with mixed noise models

2018 ◽  
Vol 54 (4) ◽  
pp. 206-208 ◽  
Author(s):  
Afeng Yang ◽  
Xue Jiang ◽  
David Day‐Uei Li
Keyword(s):  
Atmospheric Turbulence ◽  
Blind Deconvolution ◽  
Mixed Noise ◽  
Degraded Images ◽  
Noise Models

Atmospheric Turbulence Characterizationthrough Multi-Frame Blind Deconvolution

2021 ◽  
Author(s):  
Adam Webb ◽  
Michael Roggemann ◽  
Matthew Whiteley
Keyword(s):  
Atmospheric Turbulence ◽  
Blind Deconvolution

Restoring atmospheric-turbulence-degraded images

2016 ◽  
Vol 55 (19) ◽  
pp. 5082 ◽  
Author(s):  
Md. Hasan Furhad ◽  
Murat Tahtali ◽  
Andrew Lambert
Keyword(s):  
Atmospheric Turbulence ◽  
Degraded Images

Blind Image Deblurring for Multiply Image Frames Based on an Iterative Algorithm

2016 ◽  
Vol 13 (10) ◽  
pp. 6531-6538
Author(s):  
Jia Ge ◽  
Peng Xianrong ◽  
Zhang Jianlin ◽  
Fu Chengyu
Keyword(s):  
Blind Deconvolution ◽  
Object Image ◽  
Current Frame ◽  
Blind Image Deblurring ◽  
Point Spread ◽  
Spread Function ◽  
Degraded Image ◽  
Iterative Solutions ◽  
Degraded Images ◽  
Blind Image

A novel algorithm based on an iterative and nonnegative algorithm has been developed for performing blind deconvolution on multiply degraded image frames. The algorithm naturally preserves the nonnegative constraint on the iterative solutions of blind deconvolution and can produce a restored image of high resolution. Furthermore, benefited from the interframe information, the neighbouring frame can be seen as degenerated from the same object image and different point spread function (PSF), so utilizing the result of the last frame to the initial estimate of the current frame can reduce iterative times and enhance the efficiency of the algorithm, meanwhile, the algorithm is free from the instability of numerical computation. Results of applying the algorithm to simulated and real degraded images are reported.

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