Visual Saliency Guided Foveated Video Compression - Shupei Zhang; Anup Basu (IEEE Access, 2023)
Video compression has become increasingly crucial as video resolution and bitrate have surged in recent years. However, most widely applied video compression methods do not fully exploit the characteristics of the Human Visual System (HVS) to reduce perceptual redundancy in videos. In this paper, we propose a novel video compression method that integrates visual saliency information with foveation to reduce perceptual redundancy. We present a new approach to subsample and restore the input image using saliency data, which allocates more space for salient regions and less for non-salient ones. We analyze the information entropy in video frames before and after applying our algorithm and demonstrate that the proposed method reduces redundancy. Through subjective and objective evaluations, we show that our method produces videos with superior perceptual visual quality. Moreover, our approach can be added to most existing video compression standards without altering their bitstream format.