Segmentation of Synthetic Aperture Radar (SAR) Image Using Graphcut

SAR imaging technique is popular for remote sensing and monitoring
application as it offers the advantage of high resolution imagery and usability under
various weather conditions. Segmentation is important imaging processing steps in
interpretation and classification of SAR images. The process of segmentation
involving two major steps, namely feature extraction and clustering. Improving the
quality of the features will ease the burden on the clustering scheme and to solve this,
image filtering is introduced in the mothodology to improve the quality of the images.
With the variation of segmentation techniques used, final judgement indicating better
technique for SAR images application can be made. Where in this, paper, comparison
between two different techniques of segmentation are performed. They are Meanshift
Segmentation Technique and Graphcut Segmentation Technique. Evaluations of the
experiments are done to get to know which technique are better. Finally, it is come to
conclusion that Graphcut Segmentation can perform the segmentation task for SAR
images in way fastest time, which is better.