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In this paper, we present a novel unsupervised change detection scheme for multilook polarimetric synthetic aperture radar (PolSAR) images using heterogeneous clutter models. First, a multilook product model is introduced to describe the heterogeneous clutter for multilook PolSAR data, and a corresponding covariance matrix estimation method is derived. Based on this model, a new similarity measure...
Learning and then recognizing a path is a challenging task for state of the art algorithms in computer vision and robotics. In this paper, we present a new approach to visual localization along a path. Classically visual paths have been described using keyframes, single images taken at specific locations. Our method uses all the images of a path segment, Gabor-Gist and, principal component analysis...
Based on the clutter statistical characteristics of fully polarimetric SAR image, this paper presents a novel method for SAR change detection based on the heterogeneous clutter model. We use spherically invariant random vectors (SIRV) distribution model to fit the urban areas of full polarimetric images. Then, the degree of evolution between the statistical characteristics of multi temporal full SAR...
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