Wavelet packet transform basis selection method for set partitioning in hierarchical trees

2008 ◽  
Vol 17 (3) ◽  
pp. 033007 ◽  
Author(s):  
Ashraf A. Kassim
Keyword(s):  
Wavelet Packet ◽  
Selection Method ◽  
Wavelet Packet Transform ◽  
Set Partitioning ◽  
Hierarchical Trees

scholarly journals Fast Texture Synthesis in Adaptive Wavelet Packet Trees

2013 ◽  
Vol 2013 ◽  
pp. 1-8
Author(s):  
Ying-Shen Juang ◽  
Hsi-Chin Hsin ◽  
Tze-Yun Sung ◽  
Carlo Cattani
Keyword(s):  
High Frequency ◽  
Texture Synthesis ◽  
Wavelet Packet ◽  
Low Frequency ◽  
Computation Time ◽  
Wavelet Packet Transform ◽  
Synthesis Process ◽  
Adaptive Wavelet ◽  
Hierarchical Trees ◽  
Speed Up

Wavelet packet transform known as a substantial extension of wavelet transform has drawn a lot of attention to visual applications. In this paper, we advocate using adaptive wavelet packet transform for texture synthesis. The adaptive wavelet packet coefficients of an image are organized into hierarchical trees called adaptive wavelet packet trees, based on which an efficient algorithm has been proposed to speed up the synthesis process, from the low-frequency tree nodes representing the global characteristics of textures to the high-frequency tree nodes representing the local details. Experimental results show that the texture synthesis in the adaptive wavelet packet trees (TSIAWPT) algorithm is suitable for a variety of textures and is preferable in terms of computation time.

scholarly journals Adaptive Variable Degree- Zero-Trees for Re-Encoding of Perceptually Quantized Wavelet Packet Transformed Audio and High-Quality Speech

2011 ◽  
Vol 2011 ◽  
pp. 1-16
Author(s):  
Omid Ghahabi ◽  
Mohammad Hassan Savoji
Keyword(s):  
Wavelet Packet ◽  
Low Complexity ◽  
Set Partitioning ◽  
Degree Zero ◽  
Variable Degree ◽  
Audio Signals ◽  
High Quality ◽  
Scalable Algorithm ◽  
Hierarchical Trees ◽  
Zero Tree

A fast, efficient, and scalable algorithm is proposed, in this paper, for re-encoding of perceptually quantized wavelet-packet transform (WPT) coefficients of audio and high quality speech and is called “adaptive variable degree- zero-trees” (AVDZ). The quantization process is carried out by taking into account some basic perceptual considerations and achieves good subjective quality with low complexity. The performance of the proposed AVDZ algorithm is compared with two other zero-tree-based schemes comprising (1) embedded zero-tree wavelet (EZW) and (2) the set partitioning in hierarchical trees (SPIHT). Since EZW and SPIHT are designed for image compression, some modifications are incorporated in these schemes for their better matching to audio signals. It is shown that the proposed modifications can improve their performance by about 15–25%. Furthermore, it is concluded that the proposed AVDZ algorithm outperforms these modified versions in terms of both output average bit-rates and computation times.

Mistuning identification in a bladed disk using wavelet packet transform

2017 ◽  
Vol 229 (3) ◽  
pp. 1275-1295 ◽  
Author(s):  
N. Jamia ◽  
P. Rajendran ◽  
S. El-Borgi ◽  
M. I. Friswell
Keyword(s):  
Wavelet Packet ◽  
Wavelet Packet Transform ◽  
Bladed Disk

Use of Wavelet Packet Transform in Characterization of Surface Quality

2007 ◽  
Vol 46 (15) ◽  
pp. 5152-5158 ◽  
Author(s):  
J. Jay Liu ◽  
Daeyoun Kim ◽  
Chonghun Han
Keyword(s):  
Surface Quality ◽  
Wavelet Packet ◽  
Wavelet Packet Transform
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