Diagnostically lossless video compression for angiogram data using a wavelet-based texture modelling approach

David Gibson, George Tsibidis, Michael Spann, Sandra Woolley

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

This paper presents a lossy, wavelet-based approach for the compression of digital angiogram video. An analysis of the high-frequency sub-bands of a wavelet decomposition of an angiogram image reveals significantly sized regions containing no diagnostically important information. The encoding of the high-frequency sub-band wavelet coefficients in such regions proves to be burdensome, although if removed, the coefficients are notable by their absence. This paper aims to model these wavelet coefficients using a texture modeling approach. This is only performed in regions which are considered diagnostically unimportant, with diagnostically important regions encoded as normal. The effect of this procedure significantly reduces the bit-rate of diagnostically unimportant areas of the image without a perceptible loss of image quality. The effectiveness of the algorithm at different bit-rates is assessed by a consultant cardiologist with the key aim of identifying any degradation in the diagnostic content of the images.
Original languageEnglish
Pages (from-to)126-134
Number of pages9
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume4299
DOIs
Publication statusPublished - 1 Jan 2001
EventHuman Vision and Electronic Imaging VI - San Jose, United States
Duration: 20 Jan 2001 → …

Keywords

  • angiogram
  • texture
  • compression
  • wavelet
  • video

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