Research Of Remote Sensing Image Denoising Based On Wavelet Theory And Bishrink Algorithm

With the continuous development of sensor technology,aerospace technologyand data communication technology,modern remote sensing technology has entered anew phase.However,in the process of production,processing and transmission,remotesensing image will inevitably be interfered by noise.Traditional way to denoise canmake the edge of the image faint,and the Gibbs in the denoised image happensoften.In order to solve these problems,the remote sensing image denoising technologybased on the wavelet theory and BiShrink algorithm is researched in this text.In this paper,a novel BiShrink threshold and DTCWT remote sensing imagedenoising method is presented． The algorithm,take full account of the strongcorrelation between the current coefficient and parent-child coefficient and adjacentcoefficients,through the combination between the correlation intra-scale and amongscale in DTCWT to achieve the purpose of noise suppression.Experimental resultsshow the proposed algorithm gets better PSNR than other methods mentioned,observably.In terms of visual quality,the proposed algorithm can get the images withmore details,smooth profiles and restricted aliasing．Meanwhile,in order to better inhibition pseudo-Gibbs phenomenon,this paperproposes a remote sensing image denoising algorithm based on NonsubsampledContourlet Transform(NSCT) threshold shrinkage approach.It uses the correlationintra-scale in NeighShrink denoising algorithm and the correlation among scale inBiShink denoising algorithm to deal with the noise image.By using the shiftinvariance of NSCT,it suppresses the pseudo-Gibbs phenomenon.Experimental resultsshow that the proposed algorithm gets better results than other methods mentioned inthe area of PSNR and visual effect.