The search functionality is under construction.
The search functionality is under construction.

Non-recursive Discrete Periodized Wavelet Transform Using Segment Accumulation Algorithm and Reversible Round-Off Approach

Chin-Feng TSAI, Huan-Sheng WANG, King-Chu HUNG, Shih-Chang HSIA

  • Full Text Views

    0

  • Cite this

Summary :

Wavelet-based features with simplicity and high efficacy have been used in many pattern recognition (PR) applications. These features are usually generated from the wavelet coefficients of coarse levels (i.e., high octaves) in the discrete periodized wavelet transform (DPWT). In this paper, a new 1-D non-recursive DPWT (NRDPWT) is presented for real-time high octave decomposition. The new 1-D NRDPWT referred to as the 1-D RRO-NRDPWT can overcome the word-length-growth (WLG) effect based on two strategies, resisting error propagation and applying a reversible round-off linear transformation (RROLT) theorem. Finite precision performance analysis is also taken to study the word length suppression efficiency and the feature efficacy in breast lesion classification on ultrasonic images. For the realization of high octave decomposition, a segment accumulation algorithm (SAA) is also presented. The SAA is a new folding technique that can reduce multipliers and adders dramatically without the cost of increasing latency.

Publication
IEICE TRANSACTIONS on Information Vol.E91-D No.11 pp.2666-2674
Publication Date
2008/11/01
Publicized
Online ISSN
1745-1361
DOI
10.1093/ietisy/e91-d.11.2666
Type of Manuscript
PAPER
Category
VLSI Systems

Authors

Keyword