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Statistical modeling of Synthetic Aperture Radar (SAR) images is of great importance for speckle noise filtering, target detection and classification, etc. Moreover, it can provide a comprehensive understanding of terrain electromagnetics scattering mechanism. Over the past three decades, many sophisticated models have been developed for SAR images, such as(More)
Because of the disturb of trees along roads, buildings to cover, cars getting on the road an etc, it is difficult to automatically extract centerline of roads from high-resolution SAR images. This paper presents a new semi-automatic road centerline extraction method based on circular template matching. Firstly, circular template and the road orientation are(More)
Nowadays, main methods used to SAR imagery built-up areas classification are GLCM (gray-level co-occurrence matrix) textural analysis, Markov random field, etc. They are extraordinarily time consumption and need for manual interaction. In this paper, a new scheme for fast and automatic classification of built-up areas is presented. It is based on(More)
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