block compressed sensing of natural images

block compressed sensing of natural images by lu gan

There are two interesting things in this paper.

1 The measurement scheme.

2 The reconstruction method.

1 The measurement scheme.

The paper is in the context of the natural image capture (e.g. capture a image using digital camera).

The target image is divided into several blocks. For each block, a i.i.d Gaussian matrix is used as the measure matrix. Thus, the method is memory efficient and easy to be paralyzed.

2 The reconstruction method.

It is in fact hard thresholding method. They use hard thresholding and wiener filtering several times. But very interestingly, they point out that redundant frame expansions are superior than orthonormal base. e.g. wavelet + curvelet > wavelet.

plus, the POCS(projection onto convex set) is in a similar form of standard ART or sART.

[Practical signal recovery from random projections by E. Candes, etc.]