Lensless Compressive Imaging
This addresses the problem of efficient image acquisition and compression for applications like low-cost cameras, though it appears incremental in improving compressive sensing methods.
The paper tackles lensless compressive imaging by developing an architecture without lenses and an anytime reconstruction algorithm, achieving results close to JPEG compression quality with only about 10% of image pixel measurements.
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.