Perceptual quality metric guided blocking artifact reduction

Abstract

Blocking artifact reduction or deblocking algorithm is an important component in modern block-based video encoding architecture and often used as post-processing procedures in many encoding/transcoding applications. Most of the existing video deblocking algorithms do not take into account Human Visual System(HVS) models and employ empirically designed filters, resulting in suboptimal perceptual image quality and the difficulty to adjust parameters for different application scenarios. This paper presents a new deblocking algorithm that automatically generates spatially variant adaptive filters by maximizing a regularized perceptual quality metric. Such optimization based approach leads to better human perceived image quality and much easier filter parameter adjustment.