Singular value decomposition using block least mean square method for image denoising and compression
Ajay Kumar Boyat, Parth Khare · 2015
Image denoising is a well documented part of Image processing. It has always posed a problem for researchers and there is no dearth of solutions extended. Obtaining a denoised and perfectly similar image after application of processes represents a mirage that has been chased a lot. In this paper, we attempt to combine the effects of block least mean square algorithm (BLMS) to maximizes the Peak Signal to Noise Ratio (PSNR), along with singular valued decomposition (SVD), so as to achieve results that bring us closer to our aim of perfect re construction. The results showed that the combination of these methods provides easy computation, coupled with efficiency and as such is an effective way of approaching the problem.