Rough Set Based Color Channel Selection
This work addresses the need for systematic color channel selection in cloud segmentation, which is incremental as it applies an existing rough set technique to a specific domain problem.
The paper tackled the problem of color channel selection for cloud segmentation in ground-based sky camera images by proposing a rough set-based method to identify the most effective channels, resulting in improved segmentation accuracy.
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.