Multi-view in Lensless Compressive Imaging
This addresses image quality enhancement in compressive imaging for applications like surveillance or medical imaging, but appears incremental as it builds on existing compressive sensing methods.
The paper tackles the problem of reconstructing multi-view images from lensless compressive measurements using an aperture assembly with controllable transmittance patterns, achieving enhanced image quality as demonstrated in experimental results.
Multi-view images are acquired by a lensless compressive imaging architecture, which consists of an aperture assembly and multiple sensors. The aperture assembly consists of a two dimensional array of aperture elements whose transmittance can be individually controlled to implement a compressive sensing matrix. For each transmittance pattern of the aperture assembly, each of the sensors takes a measurement. The measurement vectors from the multiple sensors represent multi-view images of the same scene. We present theoretical framework for multi-view reconstruction and experimental results for enhancing quality of image using multi-view.