SNR scalable video coder using progressive transmission of DCT coefficients

Marshall A. Robers*, Lisimachos P. Kondi, Aggelos K. Katsaggelos

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

4 Scopus citations

Abstract

The importance of signal-to-noise ratio (SNR) video compression algorithms has increased in the past few years. This emergence corresponds with the vast increase of products and applications requiring the transmission of digital video streams. These new applications, including video telephony/teleconferencing, video surveillance/public safety, and video-on-demand, require limiting the bandwidth of the compressed bitstream to less than the capacity of the transmission channel. However, the channel capacity is frequently unknown at the time of compression, especially when the stream is to be broadcasted to many users over heterogeneous channels. SNR scalable compression allows a single compression to provide bitstreams of multiple quality. In this fashion, the transmitted bitrate can match the available channel(s) without requiring multiple encodings. In this paper, we present a novel approach to SNR scalable video compression. Our approach combines two separate methodologies for dividing the blocks of discrete cosine transform (DCT) coefficients. The flexible combination of these approaches allows each DCT block to be divided into a fixed number of scans while also controlling the size of each scan. Thus, the transmitted stream can contain any subset of scans from the overall compressed version and thereby both the transmitted bitrate and the quality or SNR are allowed to vary.

Original languageEnglish (US)
Pages (from-to)201-212
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume3309
Issue number1
DOIs
StatePublished - Dec 1 1998
EventVisual Communications and Image Processing '98 - San Jose, CA, United States
Duration: Jan 28 1998Jan 30 1998

Keywords

  • SNR scalable video compression
  • Spectral selection
  • Successive approximation
  • Video compression

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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