English

A Hardware Realization of Superresolution Combining Random Coding and Blurring

Image and Video Processing 2018-10-29 v1

Abstract

Resolution enhancements are often desired in imaging applications where high-resolution sensor arrays are difficult to obtain. Many computational imaging methods have been proposed to encode high-resolution scene information on low-resolution sensors by cleverly modulating light from the scene before it hits the sensor. These methods often require movement of some portion of the imaging apparatus or only acquire images up to the resolution of a modulating element. Here a technique is presented for resolving beyond the resolutions of both a pointwise-modulating mask element and a sensor array through the introduction of a controlled blur into the optical pathway. The analysis contains an intuitive and exact expression for the overall superresolvability of the system, and arguments are presented to explain how the combination of random coding and blurring makes the superresolution problem well-posed. Experimental results demonstrate that a resolution enhancement of approximately 4×4\times is possible in practice using standard optical components, without mechanical motion of the imaging apparatus, and without any a priori assumptions on scene structure.

Keywords

Cite

@article{arxiv.1810.08855,
  title  = {A Hardware Realization of Superresolution Combining Random Coding and Blurring},
  author = {Kevin Beale and Jianbo Chen and Kevin F. Kelly and Justin Romberg},
  journal= {arXiv preprint arXiv:1810.08855},
  year   = {2018}
}

Comments

12 pages, 13 figures, submitted to IEEE Transactions on Computational Imaging

R2 v1 2026-06-23T04:47:01.955Z