Perceptual Quality

Perceptual quality assessment focuses on objectively measuring how humans perceive the quality of images and videos, aiming to create models that accurately reflect subjective ratings. Current research emphasizes developing no-reference (NR) methods, particularly using deep learning architectures like transformers and diffusion models, to evaluate diverse content including high-resolution photos, 360° images, and user-generated videos. This field is crucial for improving image and video processing techniques, optimizing compression algorithms, and enhancing the user experience in various applications such as virtual reality and social media.