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Proceedings Paper

Diagnostically lossless video compression for angiogram data using a wavelet-based texture modeling approach
Author(s): David Gibson; George Tsibidis; Michael Spann; Sandra Isobel Woolley
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Paper 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.

Paper Details

Date Published: 8 June 2001
PDF: 9 pages
Proc. SPIE 4299, Human Vision and Electronic Imaging VI, (8 June 2001); doi: 10.1117/12.429482
Show Author Affiliations
David Gibson, Univ. of Birmingham (United Kingdom)
George Tsibidis, Univ. of Birmingham (United Kingdom)
Michael Spann, Univ. of Birmingham (United Kingdom)
Sandra Isobel Woolley, Univ. of Birmingham (United Kingdom)


Published in SPIE Proceedings Vol. 4299:
Human Vision and Electronic Imaging VI
Bernice E. Rogowitz; Thrasyvoulos N. Pappas, Editor(s)

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