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

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概要

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• 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.

• 2008-11-01

著者

• Wang Huan-sheng

  Department Of Computer And Communication Engineering National Kaohsiung First University Of Science

• Hsia Shih-chang

  Department Of Computer And Communication Engineering National Kaohsiung First University Of Science

• Tsai Chin-feng

  Institute Of Engineering Science And Technology National Kaohsiung First University Of Science And T

• HUNG King-Chu

  Department of Computer and Communication Engineering, National Kaohsiung First University of Science

• Hung King-chu

  Department Of Computer And Communication Engineering National Kaohsiung First University Of Science

関連論文

• Non-recursive Discrete Periodized Wavelet Transform Using Segment Accumulation Algorithm and Reversible Round-Off Approach
• A Gray Level Watermarking Algorithm Using Double Layer Hidden Approach

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