GoP-based Quality Enhancement on Video Compression.

Abstract

With recent increases in the demand for high-resolution video content, it has become increasingly challenging to transmit video data within the constraints of limited band-width. Due to the time-consuming nature of developing and disseminating new standard codecs, a large body of research has addressed improving low-quality videos through post-processing techniques. Previous studies have primarily concentrated on enhancing the quality of compressed video by addressing the temporal consistency of adjacent frames over short durations. However, these approaches often overlook specific characteristics of the video coding framework, such as notable variations in codec artifact patterns occurring at the Group of Pictures (GoP) level, which can result in considerable viewer discomfort. In this paper, we propose GoP-based Quality Enhancement (GQE), which aims to improve the quality of compressed videos by addressing issues at the GoP level. First, we present a GoP Guided Feature Propagation (GGFP) module, which addresses the root cause of the GoP level issue by propagating features from the I-frame of a different GoP to the frames currently undergoing enhancement. Then, we introduce a Temporal Aggregation (TA) module to efficiently and effectively aggregate features from the I-frame and the current frame. We extensively evaluate our model using diverse test sequences across a range of codecs, including HEVC, VP9, and AV1. Our approach not only achieves a significant reduction in the pattern shifts of GoP-level artifacts, but also demonstrates a substantial improvement in overall video quality.