.Satellite image blind restoration based on surface fitting and multivariate model[J].Optoelectronics Letters,2009,5(3):236-240 Satellite image blind restoration based on surface fitting and multivariate model 陈新兵  杨世植  王先华  乔延利 CHEN Xin-bing(Key Lab. of General Optical Radialization Calibration and Characterization Techniques of Chinese Academy of Science,Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Science, Hefei 230031, China;Graduate School of the Chinese Academy of Sci) ;YANG Shi-zhi,WANG Xian-hua,QIAO Yan-li(Key Lab. of General Optical Radialization Calibration and Characterization Techniques of Chinese Academy of Science,Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Science, Hefei 230031, China) ? Abstract:       Owing to the blurring effect from atmosphere and camera system in the satellite imaging a blind image restoration algo-rithm is proposed which includes the modulation transfer function (MTF) estimation and the image restoration. In the MTF estimation stage, based on every degradation process of satellite imaging-chain, a combined parametric model of MTF is given and used to fit the surface of normalized logarithmic amplitude spectrum of degraded image. In the image restoration stage, a maximum a posteriori (MAP) based edge-preserving image restoration method is presented which introduces multivariate Laplacian model to characterize the prior distribution of wavelet coefficients of original image. During the image restoration, in order to avoid solving high nonlinear equations, optimization transfer algorithm is adopted to decom-pose the image restoration procedure into two simple steps: Landweber iteration and wavelet thresholding denoising. In the numerical experiment, the satellite image restoration results from SPOT-5 and high resolution camera (HR) of China & Brazil earth resource satellite (CBERS-02B) ane compared, and the proposed algorithm is superior in the image edge preservation and noise inhibition. Hits: 4037 Download times: 249 View Full Text    Download reader