3D-SSIM for video quality assessment

Abstract

Effective and efficient objective video quality assessment (VQA) methods are highly desirable in modern visual communication systems for performance evaluation, quality control and resource allocation purposes. Simple VQA algorithms may be developed by direct extensions of still image quality assessment (IQA) approaches on a frame-by-frame basis. Advanced VQA methods take into account the temporal correlation and motion information contained in video signals but often lead to significantly increased computational complexity. Here we use a different approach to examine a video signal by considering it as a three-dimensional (3D) volume image. Specifically, we propose a 3D structural similarity (3D-SSIM) approach, which first creates a 3D quality map by applying SSIM evaluations within local 3D blocks, and then use local information content and local distortion based weighting methods to pool the quality map into a single quality measure. The resulting 3D-SSIM algorithm is computationally efficient and demonstrates highly competitive performance in comparison with state-of-the-art VQA algorithms when tested using four publicly available video quality databases.