블록기반 동영상 부호화에서의 웨이브렛 변환을 이용한 양자화 잡음 제거

Reduction of Quantization Noise in Block-Based Video Coding Using Wavelet Transform

In this paper, the quantization noise in block-based video coding is analyzed, and a post-processing method based on the analysis is presented for reducing the quantization noise by using a wavelet transform(WT). In the proposed method, the quantization noise is considered as the sum of a blocking noise expressed as a deterministic profile and the random remainder noise. Each noise is removed in a viewpoint of image restoration using a 1-D WT, which yields a regularized differentiation. The blocking noise first is reduced by weakening the strength of each blocking noise component that appears as an impulse in the first scale wavelet domain. The impulse strength estimation is performed using median filter, quantization parameter(QP), and local activity. The remainder noise, which is considered as a white noise at non-edge pixels, then is reduced by soft-thresholding. The experimental results show that the proposed method yields better performance in terms if subjective quality as well as PSNR performance over VM post-filter in MPEG-4 for all test sequences of various compression ratios. We also present a fast post-processing in spatial domain equivalent to that in wavelet domain for real-time application.