Improved single image non uniformity correction based on compressive
                                                                JIAN Xian zhong1,2, WANG Fan1,2, GUO Qiang3
(1.School of Optical Electrical and Computer Engineering, University of Shanghai For Science and Technology, Shanghai 200093, China;2.Shanghai Key Laboratory of Modern Optical System, Shanghai 200093, China;3.National Satellite Meteorological Center, Beijing 100081, China)

Abstract: Aiming at two major drawbacks existed in the single image non uniformity correction based on compressive sensing, which is that fairly rich information of high frequency sub bands could not be decomposed by wavelet transform and the sparse degree of images need to be known through (ROMP).A based on wavelet packet transform and sparsity adaptive compression sampling matching pursuit (CoSaSAMP) algorithm was proposed to reconstructed the image and corrected the infrared images. The improved method sparsed image by wavelet packet transform, corrected the extracted 25% pixels from original infrared image by point sampling matrix through the improved midway infrared equalization algorithm. The missing pixels was reconstructed by CoSaSAMP algorithm. The experimental results show that the proposed method was further improved in root mean square error (RMSE) and peak signal to noise ration (PSNR) compared with the single image non uniformity based on wavelet transform, the RMSE is reduced to nearly 30%, the average between each line closes to ideal image, image reconstruction are of good quality.

Key words: compressed sensing; wavelet pack; sparsity adaptive; matching pursuit; on uniformity correction