  We develop a lensless compressive imaging architecture, which consists of an
aperture assembly and a single sensor, without using any lens. An anytime
algorithm is proposed to reconstruct images from the compressive measurements;
the algorithm produces a sequence of solutions that monotonically converge to
the true signal (thus, anytime). The algorithm is developed based on the
sparsity of local overlapping patches (in the transformation domain) and
state-of-the-art results have been obtained. Experiments on real data
demonstrate that encouraging results are obtained by measuring about 10% (of
the image pixels) compressive measurements. The reconstruction results of the
proposed algorithm are compared with the JPEG compression (based on file sizes)
and the reconstructed image quality is close to the JPEG compression, in
particular at a high compression rate.

Computer Vision and Pattern Recognition;Applications;Methodology