Spatio-Temporal Video De-interlacing Algorithm Based on MAP Estimation

MAP 예측기 기반의 시공간 동영상 순차주사화 알고리즘

  • Received : 2011.06.09
  • Accepted : 2012.01.19
  • Published : 2012.03.25

Abstract

This paper presents a novel de-interlacing algorithm that can make up motion compensation errors by using maximum a posteriori (MAP) estimator. First, a proper registration is performed between a current field and its adjacent fields, and the progressive frame corresponding to the current field is found via MAP estimator based on the computed registration information. Here, in order to obtain a stable solution, well-known bilateral total variation (BTV)-based regularization is employed. Next, so-called feathering artifacts are detected on a block basis effectively. So, edge-directional interpolation is applied to the pixels where feathering artifact may happen, instead of the above-mentioned temporal de-interlacing. Experimental results show that the PSNR of the proposed algorithm is on average 4dB higher than that of previous studies and provides the better subjective quality than the previous works.

본 논문은 MAP (maximum a posterior) 예측기에 기반하여 움직임 보상 예측 오차를 보정해주는 방식의 순차주사화 (de-interlacing) 알고리즘을 제안한다. 먼저, 현재 필드와 인접한 필드 간의 적절한 정합 (registration)을 수행 한 후, 계산된 정합 정보에 기반한 MAP 예측기를 통해 현재 필드에 대응하는 순차 주사 (progressive) 프레임을 찾아낸다. 안정적인 결과를 얻기 위하여 잘 알려진 BTV (bilateral total variation) 기반의 평활화 (regularization) 과정이 추가된다. 한편, 잘못된 정합 정보로 인한 소위 깃털 현상 (feathering artifact)을 억제하기 위하여 블록 단위로 깃털 현상 발생 여부를 판단하여 발생되었다고 판단된 블록 영역에 대해서는 앞서 설명한 MAP기반 순차주사화 대신 에지 방향성에 기반한 공간적 순차주사화를 적용한다. 실험 결과에 따르면, 제안된 기법은 종래 기법들에 비하여 평균 약 4dB의 PSNR 성능 개선을 보이고 있으며, 우수한 주관적 화질을 보여주고 있다.

Keywords

References

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