Subjective Quality Assessment of Ground-based Camera Images

TL;DR

This paper introduces a new dataset of sky images for atmospheric research, emphasizing the importance of subjective quality assessment to understand how noise and distortions affect perceived image quality.

Contribution

The paper presents a novel sky image quality assessment dataset with subjective scores, enabling improved atmospheric image analysis and research.

Findings

Noise type significantly impacts perceived quality

Distortion level correlates with quality degradation

Subjective scores vary with atmospheric conditions

Abstract

Image quality assessment is critical to control and maintain the perceived quality of visual content. Both subjective and objective evaluations can be utilised, however, subjective image quality assessment is currently considered the most reliable approach. Databases containing distorted images and mean opinion scores are needed in the field of atmospheric research with a view to improve the current state-of-the-art methodologies. In this paper, we focus on using ground-based sky camera images to understand the atmospheric events. We present a new image quality assessment dataset containing original and distorted nighttime images of sky/cloud from SWINSEG database. Subjective quality assessment was carried out in controlled conditions, as recommended by the ITU. Statistical analyses of the subjective scores showed the impact of noise type and distortion level on the perceived quality.