Design of on-chip coded high-resolution 2D imaging via 3D compressed sensing

Abstract

This manuscript introduces a computational imaging approach where a static coded aperture is integrated with the image sensor to replace the extra Fourier optical elements or dynamic modulation in the previous computational high/super-resolution tasks. A two-dimensional (2D) high-resolution image with N×N pixels is formulated as a three-dimensional (3D) low-resolution cube with Nk×Nk×k2 voxels in the forward model where N is the spatial resolution and k is a factor, respectively. Thus, the 2D image reconstruction can be performed with a 3D compressed sensing model in the snapshot-compressive-imaging format which has been mathematically proved to be convergent. Our proposed method successfully performs on the scaling factors such as 4× enlargement and the PSNR gains for natural images, remote sensing images and infrared image are 1.8 dB, 3.5 dB and 1.3 dB, respectively with only 1000 paired training images.