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Adaptive Postprocessing Technique for Compressed Images using Directional Activity-based Block Analysis

방향성 활동도 기반 블록 분석을 통한 압축 영상의 적응적 후처리 기법

  • Kim, Jongho (Department of Multimedia Engineering, Sunchon National University)
  • Received : 2013.02.26
  • Accepted : 2013.04.04
  • Published : 2013.07.31

Abstract

This paper addresses an adaptive postprocessing technique to remove blocking effects of the highly compressed images. The proposed technique removes blocking effects selectively by applying filters with different strength according to block analysis based on the directional activity. One-dimensional filters which are used to remove grid noises accomplish the adaptive filtering to the signal itself as well as to the directionality of the block. Moreover, we propose a detection method of the staircase noises and corner outliers and a two-dimensional directional filter to remove them. Experimental results for various images and bitrates show that the proposed method outperforms the conventional methods in PSNR for the objective performance and GBIM for the subjective quality evaluation.

본 논문에서는 저 비트율 압축 영상의 블록킹 현상을 제거하기 위한 적응적 후처리 기법을 제안한다. 적응적 후처리는 방향성 활동도 기반의 블록 분석에 따라 다른 강도의 필터를 적용하여 블록킹 현상을 선택적으로 제거한다. 격자잡음을 제거하기 위한 1차원 필터링은 블록의 방향성뿐만 아니라 블록 내 신호의 특성에도 적응적인 필터링을 수행한다. 또한 계단형 잡음 및 모서리 잡음을 검출하는 방법 및 이를 효과적으로 제거하기 위한 2차원 방향성 필터를 제안한다. 실험 결과 다양한 영상 및 비트율에 대해서 제안한 방법의 PSNR 및 주관적 화질 평가를 위한 GBIM 결과가 기존의 블록킹 현상 제거 방법에 비해 우수한 성능을 나타냄을 확인하였다.

Keywords

References

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