Multiaperture imaging

Abstract

We study the reconstruction of a high-resolution image from multiple low-resolution images by using a nonlinear iterative backprojection algorithm. We exploit diversities in the imaging channels, namely, the number of imagers, magnification, position, rotation, and fill factor, to undo the degradation caused by the optical blur, pixel blur, and additive noise. We quantify the improvements gained by these diversities in the reconstruction process and discuss the trade-off among system parameters. As an example, for a system in which the pixel size is matched to the diffraction-limited optical blur size at a moderate detector noise level, we can reduce the reconstruction root-mean-square error by 570% by using 16 cameras and a large amount of diversity. The algorithm was implemented on a 56 camera array specifically constructed to demonstrate the resolution-enhancement capabilities. Practical issues associated with building and operating this device are presented and analyzed.

Lensfree on-chip microscopy over a wide field-of-view using pixel super-resolution

“…We should also note here that the spectral nulls of this weighting function can potentially cause aberrations in our imaging scheme for cases in which the object has a high spectral weight near those nulls. This is a well known problem in pixel super-resolution approaches, which could be addressed by multiple measurements as further discussed in [23]. …”

A switchable light field camera architecture with Angle Sensitive Pixels and dictionary-based sparse coding

“…Most objects are diffuse; a textured plane at some depth, for instance, will appear in all views of a captured light field, albeit at slightly different positions. This information can be fused using super-resolution techniques, which compute a high-resolution image from multiple subpixel-shifted, lowresolution images [28,26,5,22,25,30,7,34].…”

Prototype development and field-test results of an adaptive multiresolution PANOPTES imaging architecture

“…In a pioneering effort, Tanida et al presented the idea and proofof-concept of a system called thin observation module by bound optics (TOMBO), in which a multiaperture physical configuration is combined with digital superresolution (DSR) techniques to realize a flat form factor, high-resolution (HR) imager [1]. Likewise, various approaches to flat imaging sensors inspired by the compound eyes of insects have been explored [2][3][4][5][6][7][8]. However, none of these multiaperture imaging systems address the notion of adaptability in their designs.…”