Device, system, and method of blind deblurring and blind super-resolution utilizing internal patch recurrence

Abstract

Devices, systems, and methods of blind deblurring and blind super-resolution utilizing internal patch recurrence. Small signal patches tend to repeat 'as is' across multiple scales of a natural signal. This fractal-like behavior is utilized for signal processing tasks, including 'Blind Deblurring' or “Blind Super-Resolution”, namely, removing signal blur or increasing signal resolution without a-priori knowledge of the underlying blur kernel. While the cross-scale patch recurrence is strong in signals taken under ideal conditions, the cross-scale patch recurrence significantly diminishes when the acquisition blur deviates from an ideal blur. These deviations from ideal patch recurrences are used for recovering the underlying (unknown) blur kernel. The correct blur kernel is recovered by seeking the kernel which maximizes the patch similarity across scales of a related “reference” signal. For example, this reference signal may be the low-resolution input signal, the sharp deblurred-version of a blurry input signal, or the like. Quantitative and qualitative experiments indicate that this approach yields improved or superior results, in “Blind Deblurring” and in “Blind Super-Resolution”.