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Symmetry 2019, 11(1), 3; https://doi.org/10.3390/sym11010003

A Framework for Automatic Building Detection from Low-Contrast Satellite Images

1
College of Computer Science, Sichuan University, Chengdu 610065, China
2
School of Software Technology, Dalian University of Technology (DUT), Dalian 116621, China
*
Author to whom correspondence should be addressed.
Received: 26 September 2018 / Revised: 25 November 2018 / Accepted: 18 December 2018 / Published: 21 December 2018
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Abstract

Building detection in satellite images has been considered an essential field of research in remote sensing and computer vision. There are currently numerous techniques and algorithms used to achieve building detection performance. Different algorithms have been proposed to extract building objects from high-resolution satellite images with standard contrast. However, building detection from low-contrast satellite images to predict symmetrical findings as of past studies using normal contrast images is considered a challenging task and may play an integral role in a wide range of applications. Having received significant attention in recent years, this manuscript proposes a methodology to detect buildings from low-contrast satellite images. In an effort to enhance visualization of satellite images, in this study, first, the contrast of an image is optimized to represent all the information using singular value decomposition (SVD) based on the discrete wavelet transform (DWT). Second, a line-segment detection scheme is applied to accurately detect building line segments. Third, the detected line segments are hierarchically grouped to recognize the relationship of identified line segments, and the complete contours of the building are attained to obtain candidate rectangular buildings. In this paper, the results from the method above are compared with existing approaches based on high-resolution images with reasonable contrast. The proposed method achieves high performance thus yields more diversified and insightful results over conventional techniques. View Full-Text
Keywords: low-contrast satellite image; high-resolution satellite imagery; image equalization; building extraction; DWT–SVD; perceptual grouping low-contrast satellite image; high-resolution satellite imagery; image equalization; building extraction; DWT–SVD; perceptual grouping
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Aamir, M.; Pu, Y.-F.; Rahman, Z.; Tahir, M.; Naeem, H.; Dai, Q. A Framework for Automatic Building Detection from Low-Contrast Satellite Images. Symmetry 2019, 11, 3.

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