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Increasing the resolution of image sensors has been a never ending strugglesince many years. In this paper, we propose a novel image sensor layout whichallows for the acquisition of images at a higher resolution and improvedquality. For this, the image sensor makes use of non-regular sampling whichreduces the impact of aliasing. Therewith, it allows for capturing detailswhich would not be possible with state-of-the-art sensors of the same number ofpixels. The non-regular sampling is achieved by rotating prototype pixel cellsin a non-regular fashion. As not the whole area of the pixel cell is sensitiveto light, a non-regular spatial integration of the incident light is obtained.Based on the sensor output data, a high-resolution image can be reconstructedby performing a deconvolution with respect to the integration area and anextrapolation of the information to the insensitive regions of the pixels. Tosolve this challenging task, we introduce a novel joint sparse deconvolutionand extrapolation algorithm. The union of non-regular sampling and the proposedreconstruction allows for achieving a higher resolution and therewith animproved imaging quality.

Increasing Imaging Resolution by Non-Regular Sampling and Joint Sparse Deconvolution and Extrapolation