  Increasing the resolution of image sensors has been a never ending struggle
since many years. In this paper, we propose a novel image sensor layout which
allows for the acquisition of images at a higher resolution and improved
quality. For this, the image sensor makes use of non-regular sampling which
reduces the impact of aliasing. Therewith, it allows for capturing details
which would not be possible with state-of-the-art sensors of the same number of
pixels. The non-regular sampling is achieved by rotating prototype pixel cells
in a non-regular fashion. As not the whole area of the pixel cell is sensitive
to light, a non-regular spatial integration of the incident light is obtained.
Based on the sensor output data, a high-resolution image can be reconstructed
by performing a deconvolution with respect to the integration area and an
extrapolation of the information to the insensitive regions of the pixels. To
solve this challenging task, we introduce a novel joint sparse deconvolution
and extrapolation algorithm. The union of non-regular sampling and the proposed
reconstruction allows for achieving a higher resolution and therewith an
improved imaging quality.
