Subjective Quality Assessment of Ground-based Camera Images

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.

A Method of Ground-Based Cloud Motion Predict: CCLSTM + SR-Net

“…Ground-based cloud images have a wide range of applications in many fields, such as weather condition monitoring [3], cloud cover monitoring [4], photovoltaic power generation system [5], remote sensing and atmospheric research, air pollution and prevention [6], etc. Compared with satellite cloud images, ground-based cloud images have a smaller observation range and coverage, which can only show sky cloud conditions within a radius of tens of kilometers of the observation site.…”