Subjective Quality Assessment of Ground-based Camera Images
This work addresses the need for reliable image quality databases in atmospheric research, but it is incremental as it applies existing subjective assessment methods to a new domain-specific dataset.
The paper tackled the problem of assessing image quality for ground-based sky camera images by creating a new dataset with distorted nighttime images and conducting subjective evaluations, finding that noise type and distortion level significantly affect perceived quality.
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.