JSE_V11_N3_RP4
Multi-Temporal SAR Image Change Detection Technique Depending On NSCT Transformation and SFCM
Shamimoon Shaik
Sivappagari Chandra Mohan Reddy
Journal on Software Engineering
2230–7168
11
3
31
39
Fusion, Change Detection, Spatial Fuzzy Clustering (SFC), Non-Sub sampled Contourlet Transform (NSCT)
In this paper, an unsupervised change detection technique of multispectral images based on Non-Subsampled Contourlet Transform (NSCT) has been proposed. The proposed method fuses absolute difference and change vector analysis image using fusion rules. A fuzzy local-information C- means clustering algorithm will be proposed for classifying changed and unchanged regions in the fused difference image. The differencing, changes are measured by subtracting the intensity values pixel by pixel between the considered couple of temporal images. In the case of SAR images, the ratio operator is typically used instead of the subtraction operator since the image differencing technique is not adapted to the statistics of SAR images. The results will be proven that rationing generates better difference image for change detection using spatial fuzzy clustering approach and efficiency of this algorithm will be exhibited by sensitivity and correlation evaluation.
January - March 2017
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