Chromatic Aberration Recovery on Arbitrary Images

TL;DR

This paper presents an automatic method to minimize lateral chromatic aberration in images, improving image quality especially for high-resolution sensors, validated on artificial and real-world images.

Contribution

It introduces a robust, automatic algorithm for chromatic aberration correction applicable to arbitrary images, addressing a gap in existing optical correction methods.

Findings

Effective reduction of lateral chromatic aberration demonstrated

Algorithm performs well on both artificial and real-world images

Improves overall image quality in high-resolution imaging systems

Abstract

Digital imaging sensor technology has continued to outpace development in optical technology in modern imaging systems. The resulting quality loss attributable to lateral chromatic aberration is becoming increasingly significant as sensor resolution increases; other classes of aberration are less significant with classical image enhancement (e.g. sharpening), whereas lateral chromatic aberration becomes more significant. The goals of higher-performance and lighter lens systems drive a recent need to find new ways to overcome resulting image quality limitations. This work demonstrates the robust and automatic minimisation of lateral chromatic aberration, recovering the loss of image quality using both artificial and real-world images. A series of test images are used to validate the functioning of the algorithm, and changes across a series of real-world images are used to evaluate the performance of the approach.