Automatic Texture Optimization for 3D Urban Reconstruction

doi:10.11947/j.AGCS.2017.20160467

Abstract

Abstract: In order to solve the problem of texture optimization in 3D city reconstruction by using multi-lens oblique images, the paper presents a method of seamless texture model reconstruction. At first, it corrects the radiation information of images by camera response functions and image dark channel. Then, according to the corresponding relevance between terrain triangular mesh surface model to image, implements occlusion detection by sparse triangulation method, and establishes the triangles' texture list of visible. Finally, combines with triangles' topology relationship in 3D triangular mesh surface model and means and variances of image, constructs a graph-cuts-based texture optimization algorithm under the framework of MRF(Markov random filed), to solve the discrete label problem of texture optimization selection and clustering, ensures the consistency of the adjacent triangles in texture mapping, achieves the seamless texture reconstruction of city. The experimental results verify the validity and superiority of our proposed method.

Key words: oblique image, triangular mesh surface model, occlusion detection, graph-cuts, texture optimization

CLC Number:

P234

LI Ming, ZHANG Weilong, FAN Dingyuan. Automatic Texture Optimization for 3D Urban Reconstruction[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(3): 338-345.

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