Rough Set Based Color Channel Selection

TL;DR

This paper introduces a novel method using rough set theory to select the most effective color channels for sky and cloud segmentation in images, improving upon traditional threshold-based approaches.

Contribution

It proposes a rough set based approach for systematic color channel selection, enhancing segmentation accuracy over ad-hoc methods.

Findings

Effective identification of key color channels for sky-cloud segmentation

Improved segmentation accuracy compared to threshold-based methods

Method demonstrates robustness across different sky conditions

Abstract

Color channel selection is essential for accurate segmentation of sky and clouds in images obtained from ground-based sky cameras. Most prior works in cloud segmentation use threshold based methods on color channels selected in an ad-hoc manner. In this letter, we propose the use of rough sets for color channel selection in visible-light images. Our proposed approach assesses color channels with respect to their contribution for segmentation, and identifies the most effective ones.