Paper Info
Title
A statistical signal processing approach to image fusion for concealed weapon detection
Abstract
A statis tical signal processing approach to multisensor image fusion is presented for concealed weapon detection (CWD). This approach is based on an image formation model in which the sensor images are described as the true scene corrupted by additive non-Gaussian distortion. The expectation-maximization (EM) algorithm is used to estimate the model parameters and the fused image. We demonstrate the efficiency of this approach by applying this method to fusion of visual and non-visual images with emphasis on CWD applications.
Year
DOI
Venue
2002
10.1109/ICIP.2002.1038073
Image Processing. 2002. Proceedings. 2002 International Conference  
Keywords
Field
DocType
image processing,object detection,optimisation,sensor fusion,weapons,EM algorithm,additive nonGaussian distortion,concealed weapon detection,expectation-maximization algorithm,image formation model,model parameters estimation,multisensor image fusion,nonvisual images,statistical signal processing,visual images
Computer vision,Object detection,Multidimensional signal processing,Feature detection (computer vision),Pattern recognition,Image fusion,Computer science,Image processing,Image formation,Artificial intelligence,Statistical signal processing,Digital image processing
Conference
Volume
ISSN
Citations 
1
1522-4880
25
PageRank 
References 
Authors
1.56
4
2
Name
Order
Citations
PageRank
Jinzhong Yang11289.78
Rick S. Blum22322266.38