Adaptive quantization with spatial constraints in subband video compression using wavelets

Jiebo Luo, Chang Wen Chen, Kevin J. Parker, Thomas S. Huang

Research output: Contribution to conferencePaperpeer-review

Abstract

Coding of the high frequency subbands has been recognized as the key to the success of subband coding [1-5]. However, the existing schemes are not very efficient in exploiting the spatial and spectral localization properties resulted from wavelet-based subband decomposition. We present a novel adaptive quantization scheme with spatial constraints. This scheme is capable of exploiting simultaneously both spectrally and spatially localized characteristics of the high frequency subbands. A multi-modal Laplacian distribution is used to model the spectral distribution of a high frequency subband and a Gibbs random field is employed to model the spatial constraints. The modeling is incorporated into a non-iterative MAP estimation to yield the quantized subbands. This quantization scheme reduces significantly the activities in the high frequency bands while preserving the perceptually important structures. Such an adaptive quantization makes the entire subband video compression scheme amenable to low bit rate coding.

Original languageEnglish (US)
Pages594-597
Number of pages4
StatePublished - Jan 1 1996
Externally publishedYes
EventProceedings of the 1995 IEEE International Conference on Image Processing. Part 3 (of 3) - Washington, DC, USA
Duration: Oct 23 1995Oct 26 1995

Other

OtherProceedings of the 1995 IEEE International Conference on Image Processing. Part 3 (of 3)
CityWashington, DC, USA
Period10/23/9510/26/95

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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