# Rough Set Based Color Channel Selection

arXiv: https://arxiv.org/abs/1611.00931 · HTML: https://mlsanity.com/paper/1611.00931/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Nov 2016.

## Built on by (most cited first, 3 of 3)

- [Open-Source Ground-based Sky Image Datasets for Very Short-term Solar Forecasting, Cloud Analysis and Modeling: A Comprehensive Survey](https://mlsanity.com/paper/2211.14709/) (2022)
- [Enhancing coastal water body segmentation with Landsat Irish Coastal Segmentation (LICS) dataset](https://mlsanity.com/paper/2409.15311/) (2024)
- [Image Augmentation as Test Generation for Deep Learning-Based Image Retrieval Systems](https://mlsanity.com/paper/2608.27502/) (2026)

## Abstract (arXiv)

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.