A Content Based Region Separation and Analysis Approach for SAR Image Classification

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Hari Singh Barath, Er. Jasdeep Singh Mann


SAR images are the images captured through satellite or radar to monitor the specific geographical area or to extract any information regarding the geographical structure. This information can be used to recognize the land areas or regions with specific features such as identification of water area or flood area etc. But the images captured from satellite covers larger land regions with multiple scene pictures. To recognize the specific land area, it is required to process all the images with defined constraints to identify the particular region. The images or the image features can be trained under some classification method to categorize the land regions. There are various supervised and unsupervised classification methods to classify the SAR images. But the SAR images are high resolution images with multiple region types in same images. Because of this, the existing methods are not fully capable to classify the regions accurately. There is the requirement of more effective classification that can identify the land regions more adaptively.

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How to Cite
, H. S. B. E. J. S. M. (2018). A Content Based Region Separation and Analysis Approach for SAR Image Classification. International Journal on Recent and Innovation Trends in Computing and Communication, 6(6), 206–212. https://doi.org/10.17762/ijritcc.v6i6.1659