Automatic target recognition in SAR images using quaternion wavelet transform and principal component analysis

2017 ◽  
Vol 7 (3) ◽  
pp. 314 ◽  
Author(s):  
S. Arivazhagan ◽  
R. Ahila Priyadharshini ◽  
L. Sangeetha
Keyword(s):  
Principal Component Analysis ◽  
Wavelet Transform ◽  
Target Recognition ◽  
Principal Component ◽  
Component Analysis ◽  
Automatic Target Recognition ◽  
Sar Images ◽  
Quaternion Wavelet Transform

scholarly journals Soft Computing Based Ground Target Recognition

2020 ◽  
Vol 8 (6) ◽  
pp. 5598-5603
Keyword(s):  
Principal Component Analysis ◽  
Soft Computing ◽  
High Speed ◽  
Target Recognition ◽  
Principal Component ◽  
Component Analysis ◽  
Recognition System ◽  
Automatic Target Recognition ◽  
Kernel Functions ◽  
Support Vector

Target recognition from the data obtained from radars poses great challenge to manual analysis of the target with high speed and accuracy. So to overcome this challenge automatic target recognition system is developed using soft computing machine learning tool. The problem becomes more complex when the images are clicked from various angles. An automated classification scheme is proposed in this paper. Principal Component Analysis is used for feature extraction and to reduce the high dominions in the images data. It is known that principal component analysis is widely used from in various fields like space science. Support vector machine is used as a tool. All major kernel functions are applied to gain the maximum accuracy. This framework is evaluated and found effective as compared to results than other methods.

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