Paper
18 January 2004 Interframe wavelet video coding with operating point adaptation
Author Affiliations +
Proceedings Volume 5308, Visual Communications and Image Processing 2004; (2004) https://doi.org/10.1117/12.525695
Event: Electronic Imaging 2004, 2004, San Jose, California, United States
Abstract
Contrary to predictive schemes such as hybrid video coding systems, orthonormal transform coding systems are immune to error accumulation in case of desynchronization between encoder and decoder. Therefore, these systems allow for drift-free data adaptation at bit stream level, thus, scalability. In t+2D interframe wavelet video coding, wavelet-based motion-compensated temporal filtering is employed, followed by spatial wavelet decomposition and bit plane coding. This allows for temporal, spatial, and SNR scalability. While motion compensation seems to be essential in this scheme to achieve excellent coding performance, it causes local violation of the orthonormality of the temporal transform. Particularly, motion compensated interframe wavelet systems employ predictive coding for certain occlusion areas. In case of reference mismatch between encoder and decoder, error accumulation occurs in these regions. In this paper we present an approach to adapt the encoder operating point for predictively coded regions, effectively eliminating the reference mismatch adaptively. An iterative algorithm for computation of the decoder reference at the encoder side is presented for t+2D systems. We show that this approach significantly increases overall coding performance, gaining up to 1 dB in PSNR. Furthermore, the optimized quantization algorithm presented in an earlier work can be applied more effectively, leading to more even noise distribution.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thomas Rusert "Interframe wavelet video coding with operating point adaptation", Proc. SPIE 5308, Visual Communications and Image Processing 2004, (18 January 2004); https://doi.org/10.1117/12.525695
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KEYWORDS
Computer programming

Quantization

Video coding

Wavelets

Discrete wavelet transforms

Reconstruction algorithms

Signal to noise ratio

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