Abstract: Compressed sensing is new technique for an efficient data acquisition.in this paper, we proposed, a multi- scale variant of block compressed sensing of images coupled with Smoothed Projected Landweber Reconstruction. In essence, block-based compressed sampling is deployed independently with each subband of each decomposition level of a wavelet transform of an image. The corresponding multi-scale reconstruction interleaves Landweber steps on the individual blocks with a smoothing filter in the spatial domain of the image and thresholding within a sparsity transform. Experimental results shows that the proposed multi-scale reconstruction outperform over original block compressed sensing with Smoothed Projected Landweber.
Keywords: Compressed sensing, bivariate shrinkage, smoothing filter.