Change Detection in SAR Images using Image Fusion and Supervised Classifier
K.R. Khandarkar1, Sharvari C. Tamane2
1Mr. K.R. Khandarkar, Department of Computer Engineering, Research Scholar, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, India.
2Dr. Sharvari C. Tamane , Department of Information Technology, JNEC, Aurangabad, India
Manuscript received on April 02, 2020. | Revised Manuscript received on April 15, 2020. | Manuscript published on May 30, 2020. | PP: 685-687 | Volume-9 Issue-1, May 2020. | Retrieval Number: D8779118419/2020©BEIESP | DOI: 10.35940/ijrte.D8779.059120
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The paper proposes an approach based on a fusion object and a supervised classification system to improve detection f or SAR images. Here we are using CNN denoising method for removing noise in the input image. Then information from first image is processed using mean_ ratio operator. Second image is processed by log ratio operator. These two images are fused using PCA algorithm and the output is provided to KNN supervised classifier for finding change detection in the image.
Keywords: SAR (Synthetic-Aperture-Radar), difference image, image-fusion, CDA (change_ Detection_ algorithms), CNN.
Scope of the Article: Classification