Extraction of Straight Lines in Aerial Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Marked Point Process of Rectangles and Segments for Automatic Analysis of Digital Elevation Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmentation Framework Based on Label Field Fusion
IEEE Transactions on Image Processing
Archaeological trace extraction by a local directional active contour approach
Pattern Recognition
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We propose a new approach at the rectangle feature level to extract buildings from high-resolution polarimetric synthetic aperture radar (PolSAR) data, using both region-based and edge-based information. The first step employs low-level detectors to provide raw region and edge information of the scene. In the second step, the rectangle features are initially extracted from the edge detection results, and further optimized to best fit the rough region-based building detection results. In the last step, a novel Markov random field (MRF) framework for rectangles is proposed, in which the data energy term of rectangles is defined from the region information while the smoothness term is defined according to the contextual prior knowledge about the buildings. Under this framework, the building rectangles are identified from the optimized rectangle candidates by minimizing the total energy. The effectiveness of the proposed method is verified using the real fully PolSAR data.