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Proceedings Paper

Bit-plane based analysis of integer wavelet coefficients for image compression
Author(s): Ahmed Abu-Hajar
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Paper Abstract

This paper presents bit-plane based statistical study for integer wavelet transforms commonly used in image compression. In each bit-plane, the coefficients were modeled as binary random variables. Experimental results indicate the probability of the significant coefficients (P1), in each bit-plane, monotonically increases from P1 ≈ 0 at the most significant bits (MSB) to P1≈ 0.5 at the least significant bits (LSB). Then, a parameterized model to predict P1 from the MSB to the LSB was proposed. Also, the correlation among the different bit-planes within the same coefficient was investigated. In addition, this study showed correlation of the significant coefficients in the same spatial orientation among different subbands. Finally, clustering within the each subband and across the different subband with the same spatial orientation was investigated. Our results show strong correlation of previously coded significant coefficients at higher levels and the significant coefficients in future passes at lower levels. The overall study of this paper is useful in understanding and enhancing existing wavelet-based image compression algorithms such as SPIHT and EBC.

Paper Details

Date Published: 16 January 2006
PDF: 9 pages
Proc. SPIE 6060, Visualization and Data Analysis 2006, 60600D (16 January 2006); doi: 10.1117/12.641521
Show Author Affiliations
Ahmed Abu-Hajar, Digitavid (United States)

Published in SPIE Proceedings Vol. 6060:
Visualization and Data Analysis 2006
Robert F. Erbacher; Jonathan C. Roberts; Matti T. Gröhn; Katy Börner, Editor(s)

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