A new building recognition algorithm from high resolution remote sensing imagery

Z. Chen; G. Y. Wang; J. G. Liu; C. J. Cheng; J. H. Deng

doi:10.1117/12.901793

23 November 2011 A new building recognition algorithm from high resolution remote sensing imagery

Z. Chen, G. Y. Wang, J. G. Liu, C. J. Cheng, J. H. Deng

Proceedings Volume 8006, MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications; 80060L (2011) https://doi.org/10.1117/12.901793
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China

Abstract

The building recognition from high resolution remote sensing images is an internationally advanced research field. But there are still many difficult to be solved. In this paper, in order to extract and recognize the special building from the high resolution remote sensing images, a new algorithm is presented. First, a self-adaptive Average Absolute Difference Maximum edge enhancement algorithm is presented to enhance the edge of the building and suppress the background at one time. Second, the locally self-adaptive segmentation algorithm is implemented to obtain the binary image. Third, the thinning algorithm is implanted to obtain the single pixel edge of the building and a pruning algorithm is necessary in order to reduce the computation times in the following process. The following step is obtained by the Hough transformation to make the edge of the building into polygon. Finally, an Interior angle chain (IAC) is proposed to recognize the building with different shape. The experimental results demonstrate that the new algorithm can extract the special shape building quickly and accurately.

Citation Download Citation

Z. Chen, G. Y. Wang, J. G. Liu, C. J. Cheng, and J. H. Deng "A new building recognition algorithm from high resolution remote sensing imagery", Proc. SPIE 8006, MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 80060L (23 November 2011); https://doi.org/10.1117/12.901793

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