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Artificial Intelligence based Image Classification of Synthetic Aperture Radar

G. B. Giri*, P. M. Menghal**

*-** Department of Radar & Control System, Faculty of Electronics, Military College of Electronics & Mechanical Engineering, Secunderabad, Telangana, India.

Periodicity:October - December'2020
DOI : https://doi.org/10.26634/jip.7.4.17341

Abstract

Synthetic Aperture Radar (SAR) imaging has been an exciting field owing to its wide application in military/non military fields. This paper is aimed at investigating effects of using different types of signals and emission parameters on the accuracy and resolution of simulated SAR image and performing simulation on a reconstructed SAR image of an fully polarimetric SAR for identifying different land features. The speckles in the image are removed using the Lee filter and then the image is decomposed using Pauli decomposition method. After feature extraction, neural network techniques are used for training, validating and testing the network. The final image classified in RGB, representing features like urban, vegetation and water has been achieved. The percentage classification of each feature pixels in the image has been presented using confusion matrix.

Keywords

Synthetic Aperature Radar (SAR), Confusion Matrix, Lee Filter Method, Pauli Decomposition Method.

How to Cite this Article?

Giri, G. B., and Menghal, P. M. (2020). Artificial Intelligence based Image Classification of Synthetic Aperture Radar. i-manager's Journal on Image Processing, 7(4), 1-9. https://doi.org/10.26634/jip.7.4.17341

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