A low-rank approach to image defringing

TL;DR

This paper introduces a novel low-rank based method for removing interference fringe patterns from near-infrared CCD images, improving upon traditional techniques by estimating patterns globally across multiple images without external data.

Contribution

The paper presents a new low-rank approach to estimate and remove fringe patterns in CCD images, accommodating pattern variations and eliminating the need for external calibration data.

Findings

Effective fringe removal demonstrated on CFHT Megacam images

Method accommodates pattern variations across images

Outperforms traditional fringe correction techniques

Abstract

In this work, we revisit the problem of interference fringe patterns in CCD chips occurring in near-infrared bands due to multiple light reflections within the chip. We briefly discuss the traditional approaches that were developed to remove these patterns from science images, and mention their limitations. We then introduce a new method to globally estimate the fringe patterns in a collection of science images without additional external data, allowing for some variation of the patterns between images. We demonstrate this new method on near-infrared images taken by the CFHT wide-field imager Megacam.