Image Adaptive Denoising Method Based on Compressive Sensing

Lin Zhang; Xia Ling Zeng; Sun Li

doi:10.4028/www.scientific.net/AMM.635-637.993

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 635-637Image Adaptive Denoising Method Based on...

Image Adaptive Denoising Method Based on Compressive Sensing

Abstract:

We present a new adaptive denosing method using compressive sensing (CS) and genetic algorithm (GA). We use Regularized Orthogonal Matching Pursuit (ROMP) to remove the noise of image. ROMP algorithm has the advantage of correct performance, stability and fast speed. In order to obtain the optimal denoising effect, we determine the values of the parameters of ROMP by GA. Experimental results show that the proposed method can remove the noise of image effectively. Compared with other traditional methods, the new method retains the most abundant edge information and important details of the image. Therefore, our method has optimal image quality and a good performance on PSNR.