Work

Hybrid Cloud Segmentation Approach Combining YOLOv8 Instance Segmentation with HSV Thresholding for Multi-Site Assessment

Year: 2026

Type: article

Abstract: Accurate cloud segmentation from ground-based fisheye camera imagery is essential for solar irradiance forecasting and photovoltaic system optimization. Traditional computer vision approaches, such as HSV thresholding and K-means clustering, face significant limitations when applied globally to sky images due to the spectral similarity between cloud regions and sky areas under varying atmospheric conditions. This study presents a hybrid methodology that leverages YOLOv8 instance segmentation to provide contextual cloud regions followed by refined HSV thresholding within these detected areas. The approach incorporates solar trajectory modeling using pvlib for accurate sun disk detection and exclusion, preventing false cloud classification. The methodology was developed and validated at the CIESOL using Mobotix Q71 fisheye cameras, and later tested in Antofagasta (Chile) and Huelva (Spain). The YOLOv8l-seg model achieved a mask precision of 0.821 and box [email protected] of 0.680 on validation data. The results show a promising correlation with radiometric measurements such as clearness index kt and diffuse fraction kd in preliminary validation cases. While YOLOv8 demonstrates good cross-site generalization, HSV thresholding requires camera-specific calibration for optimal performance. The method addresses the context-dependency limitations of traditional algorithms, though computational performance and broader validation remain areas for future work.

Source: Remote Sensing

DOI: 10.3390/rs18172869

Authors: Augustin Alexandru Besu, Enrique García-Campos, Gabriel López, Mauricio Trigo-González, Joaquín Alonso-Montesinos

Institutions: University of Almería, Universidad de Huelva, Universidad de Antofagasta

Language: English

Topic: Solar Radiation and Photovoltaics

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Climate action

Open Access status: gold

Estimated APC paid: $3,258