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15 October 2015 Information theoretic SAR boundary detection with user interaction
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Detection of region boundaries is a very challenging task especially in the presence of noise or speckle as in synthetic aperture radar images. In this work, we propose a user interaction based boundary detection technique which makes use of B-splines and well-known powerful tools of information theory such as the Kullback-Leibler divergence (KLD) and Bhattacharyya distance. The proposed architecture consists of the following four main steps: (1) The user selects points inside and outside of a region. (2) Profiles that link these inside and outside points are extracted. (3) Boundary points that lie on the profile are located. (4) Finally, the B-splines that provide both elasticity and smoothness are used connect boundary points together to obtain an accurate estimate of the actual boundary. Existing work related to this approach are extended in several axes. First the use of multiple points both inside and outside of a region made possible to obtain a few times more boundary points. A tracking stage is proposed to put the boundary points in the right order and at the same time eliminate some of them that are erroneously detected as boundary points as well. Experiments were conducted using simulated and real SAR images.
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Can Demirkesen and Uğur Murat Leloğlu "Information theoretic SAR boundary detection with user interaction", Proc. SPIE 9643, Image and Signal Processing for Remote Sensing XXI, 964319 (15 October 2015);


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