화소 영역 Wyner-Ziv코덱에서 적응적 예측을 통한 보조정보 생성 방식과 성능 비교

Abstract

DVC (Distributed Video Coding) allows us to explore the video statistics at the decoder side, resulting in a less complex encoder and more complex decoder. In this approach, it is important to generate a good prediction to the current Wyner-Ziv frame, called side information, which plays a crucial role in the overall performance of a DVC system. Conventional MCFI (motion compensated frame interpolation) techniques, which explore temporal correlations between neighbor frames of the current frame, preform the block-based or object-based motion estimation, but, they do not include the basis frame for the Wyner-Ziv frame. This paper proposes an efficient way to get better side information, by finding the average frame between neighbor frames and by comparing adaptively the candidate blocks. Through computer simulations, it is shown that the proposed method can improve the performance up to 0.4dB and provide better subjective and objective visual qualities in Wyner-Ziv CODEC.