Recently, several low and mid-level vision algorithms have been successfully demonstrated at high-frame rate on a low power-budget using compact programmable CPA (Cellular Processor Arrays) vision-chips that embed a Processing Element (PE) at each pixel. Because of the inherent constraint in the VLSI design of these devices, algorithms they run are limited to scarce resources, in particular memory - that is the number of registers available per pixel. In this work, we propose an algorithmic procedure to trade off the pixel resolution of a programmable CPA vision-chip against the number of its registers. By grouping pixels into “super-pixels” where pixel registers are interlaced, we virtually expose more registers in software allowing to run more sophisticated algorithms. We implement and demonstrate on an actual device an algorithm that could not have been executed on an existing CPA at full resolution due to its memory requirements.