  Increasing spatial image resolution is an often required, yet challenging
task in image acquisition. Recently, it has been shown that it is possible to
obtain a high resolution image by covering a low resolution sensor with a
non-regular sampling mask. Due to the masking, however, some pixel information
in the resulting high resolution image is not available and has to be
reconstructed by an efficient image reconstruction algorithm in order to get a
fully reconstructed high resolution image. In this paper, the influence of
different sampling masks with a reduced randomness of the non-regularity on the
image reconstruction process is evaluated. Simulation results show that it is
sufficient to use sampling masks that are non-regular only on a smaller scale.
These sampling masks lead to a visually noticeable gain in PSNR compared to
arbitrary chosen sampling masks which are non-regular over the whole image
sensor size. At the same time, they simplify the manufacturing process and
allow for efficient storage.
