Speech recognition based on wavelet packet transform and K-L expansion

2008 ◽  
Author(s):  
Xu Wang ◽  
Zhiyan Han ◽  
Jian Wang ◽  
Yujuan Ma
Keyword(s):  
Speech Recognition ◽  
Wavelet Packet ◽  
Wavelet Packet Transform

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

FUSION OF SURVEILLANCE IMAGES IN INFRARED AND VISIBLE BAND USING CURVELET, WAVELET AND WAVELET PACKET TRANSFORM

2010 ◽  
Vol 08 (02) ◽  
pp. 271-292 ◽  
Author(s):  
PARUL SHAH ◽  
S. N. MERCHANT ◽  
U. B. DESAI
Keyword(s):  
Wavelet Packet ◽  
Curvelet Transform ◽  
Visual Quality ◽  
Wavelet Packet Transform ◽  
Discrete Wavelet ◽  
Discrete Wavelet Packet Transform ◽  
Fused Image ◽  
Fusion Methods ◽  
Visible Images

This paper presents two methods for fusion of infrared (IR) and visible surveillance images. The first method combines Curvelet Transform (CT) with Discrete Wavelet Transform (DWT). As wavelets do not represent long edges well while curvelets are challenged with small features, our objective is to combine both to achieve better performance. The second approach uses Discrete Wavelet Packet Transform (DWPT), which provides multiresolution in high frequency band as well and hence helps in handling edges better. The performance of the proposed methods have been extensively tested for a number of multimodal surveillance images and compared with various existing transform domain fusion methods. Experimental results show that evaluation based on entropy, gradient, contrast etc., the criteria normally used, are not enough, as in some cases, these criteria are not consistent with the visual quality. It also demonstrates that the Petrovic and Xydeas image fusion metric is a more appropriate criterion for fusion of IR and visible images, as in all the tested fused images, visual quality agrees with the Petrovic and Xydeas metric evaluation. The analysis shows that there is significant increase in the quality of fused image, both visually and quantitatively. The major achievement of the proposed fusion methods is its reduced artifacts, one of the most desired feature for fusion used in surveillance applications.

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