Smear correction of highly-variable, frame-transfer-CCD images with application to polarimetry

TL;DR

This paper introduces a new smear correction algorithm for frame-transfer CCD images that accounts for significant intensity variations between frames, improving image quality in fast polarimetric imaging.

Contribution

The paper reformulates the smear model to include variable illumination, providing a novel desmearing expression and noise analysis tailored for high-speed polarimetry.

Findings

Effective smear correction in highly-variable images

Improved image quality in fast polarimetric applications

Validated noise properties of the new model

Abstract

Image smear, produced by the shutter-less operation of frame transfer CCD detectors, can be detrimental for many imaging applications. Existing algorithms used to numerically remove smear, do not contemplate cases where intensity levels change considerably between consecutive frame exposures. In this report we reformulate the smearing model to include specific variations of the sensor illumination. The corresponding desmearing expression and its noise properties are also presented and demonstrated in the context of fast imaging polarimetry.