Volume 10 Issue 2 - April 2018

  • 1. Flooded areas detection technique using cross normalization method

    Authors : Suman T. Jadhav, Kailash J. Karande

    Pages : 121-125

    DOI : http://dx.doi.org/10.21172/1.102.19

    Keywords : Flood detection, image enhancement, multitemporal synthetic aperture radar (SAR) imagery, RGB composition, Cross-calibration/normalization.

    Abstract :

    The problem of detection of flooded areas from multitemporal SAR images is addressed here. Different image processing methods for synthetic Aperture Radar (SAR) images have been presented in order to identify flooded areas after a flood event. Multitemporal image analysis methods are applied to a pair of SAR images, acquired on the same area at different times. SAR calibration is a very complex and sensitive problem; some errors may persist after calibration that interferes with subsequent steps in the data fusion and visualization process. “Cross-calibration/normalization,” method is proposed to solve this problem. This, in turn, facilitates image enhancement and the numerical comparison of different images with data fusion and visualization processes. The proposed processing chain includes filtering, histogram truncation, and equalization steps applied in an adaptive way to the images. Fast-ready flooded maps have been generated by an RGB composition that is able to enhance the changes occurred. Pre-flood and post-flood images are combined into a color image to better identify the flooded areas in comparison with permanent water and other classes. “Fast-ready flood map,” are very quickly and automatically generated without user interaction to support the authorities in providing first aid to the population.

    Citing this Journal Article :

    Suman T. Jadhav, Kailash J. Karande, "Flooded areas detection technique using cross normalization method ", https://www.ijltet.org/journal_details.php?id=930&j_id=4479, Volume 10 Issue 2 - April 2018, 121-125, #ijltetorg