James E. Fowler — Publications
J. E. Fowler, S. Mun, and E. W. Tramel, “Multiscale Block Compressed Sensing with Smoothed Projected Landweber Reconstruction,” in Proceedings of the European Signal Processing Conference, Barcelona, Spain, August 2011, pp. 564-568.
A multiscale variant of the block compressed sensing with smoothed projected Landweber reconstruction algorithm is proposed for the compressed sensing of images. In essence, block-based compressed-sensing sampling is deployed independently within each subband of each decomposition level of a wavelet transform of an image. The corresponding multiscale reconstruction interleaves Landweber steps on the individual blocks with a smoothing filter in the spatial domain of the image as well as thresholding within a sparsity transform. Experimental results reveal that the proposed multiscale reconstruction preserves the fast computation associated with block-based compressed sensing while rivaling the reconstruction quality of a popular total-variation algorithm known for both its high-quality reconstruction as well as its exceedingly large computational cost.
- Source Code: See the BCS-SPL website.