Title: Automatic building extraction based on improved watershed segmentation, mutual information match and snake model
Authors: Gang Li; Jinliang An; Youchuan Wan
Addresses: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan city, Hubei Province 430079, China. ' College of Information Technology, Henan Institute of Science and Technology, Xinxiang city, Henan Province 453003, China. ' School of Remote Sensing and Information Engineering, Wuhan University, Wuhan city, Hubei Province 430079, China
Abstract: Automatic building extraction from high resolution remote sensing image has been a research hotspot. It is also a recognised difficulty because of the diversity and complexity of building structures. This paper proposes a new method for automatic building extraction based on improved watershed segmentation, mutual information match and improved snake model. Our method was divided into four stages, which were homogenous region generation, building template extraction, candidate building region selection and building boundary determination. Firstly, an improved watershed segmentation algorithm was proposed. The improvements included the adaptive de-noising method based on wavelet transformation and the marker extraction based on gradient flatness index. Secondly, building templates were extracted based on shape features and shape restrictions. Thirdly, candidate building regions were selected based on mutual information match. Finally, the traditional snake model was improved in two aspects: automatic determination of initial snake contour and new energy equation. According to the experiment results, our method can improve the accuracy of building extraction, and almost all the buildings are extracted correctly.
Keywords: building extraction; improved watershed segmentation; mutual information match; snake model; adaptive wavelet de-noising; modelling; remote sensing images; wavelet transforms; gradient flatness index; shape features; shape restrictions.
International Journal of Computer Applications in Technology, 2012 Vol.43 No.2, pp.147 - 154
Received: 08 May 2021
Accepted: 12 May 2021
Published online: 24 Mar 2012 *