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

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 x N pixels is formulated as a three-dimensional (3D) low-resolution cube with Nk x Nk x 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 4x 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.