M.K.Naskar

Work place: Electronics and Tele-Communication Dept. Jadavpur University, Kolkata, West Bengal,India Correspondence to: Pushan Kumar Dutta

E-mail: ascendent1@gmail.com

Website:

Research Interests: Computer Networks, Embedded System, Computer systems and computational processes

Biography

Dr M .K Naskar is currently Professor in the Department of Electronics and Telecommunications Engineering, Jadavpur University, Kolkata, India and in-charge of the “Advanced Digital and Embedded Systems Lab”. His research interests include Wireless Sensor Networks, Optical Networks and Embedded Systems.

Author Articles
A Method for Post-hazard Assessment Through Topography Analysis using Regional Segmentation for Multi-temporal Satellite Imagery: A Case Study of 2011 Tohuku Earthquake Region

By Pushan Kumar Dutta O.P. Mishra M.K.Naskar

DOI: https://doi.org/10.5815/ijigsp.2013.10.08, Pub. Date: 8 Aug. 2013

Non-rigid image registration in extracting deformation map for two satellite images of the same region before and after earthquake occurrence based on measure of intensity dissimilarity C(Ir, T(If)) can play a significant role in post hazard analysis. In this paper, we have proposed a novel image transformation and regional segmentation of the same visualized region by assigning displacement label to change in intensity using Advanced Synthetic Aperture Radar (ASAR) satellite images. We used graph cut based non rigid registraion with a data term and a smoothness term for assigning markovianity between neighboring pixels. Displacement labels has been directly assigned from this data term for small intensity difference. Secondly, our data term imposes stricter penalty for intensity mismatches and hence yields higher registration accuracy.
Based on the satellite image analysis through image segmentation, it is found that the area of .997 km2 for the Honshu region was a maximum damage zone localized in the coastal belt of NE Japan fore-arc region. A further objective has been to correlate fractal analysis of seismic clustering behavior with image segmentation suggesting that increase in the fractal dimension coefficient is associated with the deviation of the pixel values that gives a metric of the devastation of the de-clustered region.

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