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Proceedings Paper

Priorization of region-of-interest (ROI) using embedded coding of wavelet coefficients
Author(s): Luc Martel; Andre Zaccarin
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Paper Abstract

This paper addresses the problem of prioritizing, i.e., preserve with higher fidelity, region-of-interest during image compression. Regions-of-interest are found, for example, in medical imagery where only a small area is useful for diagnostic, or in surveillance images where targets have to be identified and tracked. These ROI are often characterized by their fine details which therefore need to be preserved if the image is to be of any use after it is decompressed. Wavelet- based image compression is appropriate for such tasks because of its localization property. We present an algorithm, based on Shapiro's popular EZW (Embedded image coding using Zerotree of Wavelet coefficients) to prioritize region-of-interest. A non-uniform quantizer with smaller steps for smaller coefficients is used on the coefficients of the ROI. This allows to transmit initially the fine details of the ROI and to use successive approximation quantization to reduce the quantization error on larger coefficients of the image, ROI or non-ROI. Simulation results show that this approach allows to efficiently preserve the fine details of the ROI.

Paper Details

Date Published: 17 July 1998
PDF: 12 pages
Proc. SPIE 3374, Signal Processing, Sensor Fusion, and Target Recognition VII, (17 July 1998); doi: 10.1117/12.327103
Show Author Affiliations
Luc Martel, Univ. Laval (Canada)
Andre Zaccarin, Univ. Laval (United States)

Published in SPIE Proceedings Vol. 3374:
Signal Processing, Sensor Fusion, and Target Recognition VII
Ivan Kadar, Editor(s)

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