In this paper, we present a semi-automatic road extraction method based on a piecewise parabola model with 0-order continuity. The piecewise parabola model is constructed by seed points coarsely placed by a human operator. In this case, road extraction actually becomes a physical problem of solving of each piece of parabola with only two or three unknown parameters by using image constraints. We have used a least square template matching to solve the parabola parameters. The template is deformable developed based on the automatic detection of dual road edges. In addition, a method of flexible observation weight evaluation has also been developed in this matching method. Extensive testing experiments on various image sets demonstrate that the method is able to extract road centerlines reliably. It offers much higher efficiency in contrast to manual digitizing process. We also discuss some issues about semiautomatic road extraction and future work for improving the reliability and extending the availability of our method.

Intelligent seamline selection for image mosaicking is an area of active research in the fields of massive data processing, computer vision, photogrammetry and remote sensing. In mosaicking applications for digital orthophoto maps (DOMs), the visual transition in mosaics is mainly caused by differences in positioning accuracy, image tone and relief displacement of high ground objects between overlapping DOMs. Among these three factors, relief displacement, which prevents the seamless mosaicking of images, is relatively more difficult to address. To minimize visual discontinuities, many optimization algorithms have been studied for the automatic selection of seamlines to avoid high ground objects. Thus, a new automatic seamline selection algorithm using a digital surface model (DSM) is proposed. The main idea of this algorithm is to guide a seamline toward a low area on the basis of the elevation information in a DSM. Given that the elevation of a DSM is not completely synchronous with a DOM, a new model, called the orthoimage elevation synchronous model (OESM), is derived and introduced. OESM can accurately reflect the elevation information for each DOM unit. Through the morphological processing of the OESM data in the overlapping area, an initial path network is obtained for seamline selection. Subsequently, a cost function is defined on the basis of several measurements, and Dijkstra's algorithm is adopted to determine the least-cost path from the initial network. Finally, the proposed algorithm is employed for automatic seamline network construction; the effective mosaic polygon of each image is determined, and a seamless mosaic is generated. The experiments with three different datasets indicate that the proposed method OPEN ACCESS Remote Sens. 2014, 6 12335 meets the requirements for seamline network construction. In comparative trials, the generated seamlines pass through fewer ground objects with low time consumption.

Three‐dimensional (3D) reconstruction and texture mapping of buildings or other man‐made objects are key aspects for 3D city landscapes. An effective coarse‐to‐fine approach for 3D building model generation and texture mapping based on digital photogrammetric techniques is proposed. Three video image sequences, two oblique views of building walls and one vertical view of building roofs, acquired by a digital video camera mounted on a helicopter, are used as input images. Lidar data and a coarse two‐dimensional (2D) digital vector map used for car navigation are also used as information sources. Automatic aerial triangulation (AAT) suitable for a high overlap image sequence is used to give initial values of camera parameters of each image. To obtain accurate image lines, the correspondence between outlines of the building and their line features in the image sequences is determined with a coarse‐to‐fine strategy. A hybrid point/line bundle adjustment is used to ensure the stability and accuracy of reconstruction. Reconstructed buildings with fine textures superimposed on a digital elevation model (DEM) and ortho‐image are realistically visualised. Experimental results show that the proposed approach of 3D city model generation has a promising future in many applications.

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