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Proceedings Paper

B-term approximation using tree-structured Haar transforms
Author(s): Hsin-Han Ho; Karen O. Egiazarian; Sanjit K. Mitra
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Paper Abstract

We present a heuristic solution for B-term approximation using Tree-Structured Haar (TSH) transforms. Our solution consists of two main stages: best basis selection and greedy approximation. In addition, when approximating the same signal with different B constraint or error metric, our solution also provides the flexibility of having less overall running time at expense of more storage space. We adopted lattice structure to index basis vectors, so that one index value can fully specify a basis vector. Based on the concept of fast computation of TSH transform by butterfly network, we also developed an algorithm for directly deriving butterfly parameters and incorporated it into our solution. Results show that, when the error metric is normalized ℓ1-norm and normalized ℓ2-norm, our solution has comparable (sometimes better) approximation quality with prior data synopsis algorithms.

Paper Details

Date Published: 11 February 2009
PDF: 10 pages
Proc. SPIE 7245, Image Processing: Algorithms and Systems VII, 724505 (11 February 2009); doi: 10.1117/12.816680
Show Author Affiliations
Hsin-Han Ho, Univ. of California, Santa Barbara (United States)
Karen O. Egiazarian, Tampere Univ. of Technology (Finland)
Sanjit K. Mitra, Univ. of California, Santa Barbara (United States)


Published in SPIE Proceedings Vol. 7245:
Image Processing: Algorithms and Systems VII
Nasser M. Nasrabadi; Syed A. Rizvi; Jaakko T. Astola; Karen O. Egiazarian, Editor(s)

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