Atmospheric Turbulence-Degraded Image Blind Restoration Method Using the Accelerated and Regularized RL Algorithm

Abstract

Abstract:

A turbulence-degraded image blind restoration method (AccRLTV-IBD) using accelerated and regularized Richardson-Lucy(RL) algorithm is proposed. The accelerated and regularized RL (AccRLTV) algorithm is based on total variation (TV) regularized RL algorithm and vector extrapolation acceleration technique. The observed image or the physical model of long exposure atmospheric turbulence optical transfer function (OTF) is used to obtain the initial point spread function (PSF), and a non-reference restored image quality evaluation criterion called relative gray mean grads (RGMG) is defined on the basis of other evaluation criterion called gray mean grads (GMG). The restored images of simulation data and real turbulence-degraded data show that the IBD method based on RL is better than the IBD method based on Wiener, and AccRLTV-IBD, compared with RL-IBD algorithm, has greater convergence rate and better restoration result.

Key words: image restoration, atmospheric turbulence-degraded image, iterative blind deconvolution, Richardson-Lucy algorithm, vector extrapolation acceleration technique, total variation regularization

CLC Number:

TP391.41

LI Yong, FAN Cheng-yu, SHI Dong-feng. Atmospheric Turbulence-Degraded Image Blind Restoration Method Using the Accelerated and Regularized RL Algorithm[J]. Journal of Atmospheric and Environmental Optics, 2011, 6(5): 342-350.

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