Deringing cartoons by image analogies

Abstract

In this article, we propose a novel method to reduce ringing artifacts in BDCT-encoded cartoon images using image analogies. The quantization procedure of BDCT compression (such as JPEG and MPEG) introduces annoying visual artifacts. Our main focus is on the removal of ringing artifacts that is seldom addressed by existing methods. In the proposed method, the contaminated image is modeled as a Markov random field (MRF). We “learn” the behavior of contamination by extracting massive numbers of artifact patterns from a training set, and organizing them using tree-structured vector quantization (TSVQ). Instead of postfiltering the input contaminated image, we synthesize an artifact-reduced image. Our method is noniterative and hence, can remove artifacts within a very short period of time. We show that substantial improvement is achieved using the proposed method in terms of visual quality and statistics.