Research Papers

Thresholding-based remote sensing image segmentation using mean absolute deviation algorithm

[+] Author Affiliations
Libao Zhang

Beijing Normal University, College of Information Science and Technology, No. 19 Xinjiekouwai Street, Haidian District, Beijing 100875, China

Aoxue Li

Beijing Normal University, College of Information Science and Technology, No. 19 Xinjiekouwai Street, Haidian District, Beijing 100875, China

J. Appl. Remote Sens. 8(1), 083542 (Oct 27, 2014). doi:10.1117/1.JRS.8.083542
History: Received April 9, 2014; Revised September 19, 2014; Accepted September 24, 2014
Text Size: A A A

Abstract.  Simple and effective segmentation algorithms are required for remote sensing images because of their mass data and complex texture features. An algorithm based on minimum class mean absolute deviation (MCMAD) is proposed. First, a two-dimensional (2-D) histogram is constructed by a median filter and gray process. Second, by using a diagonal projection, the 2-D histogram of remote sensing images is transformed into a one-dimensional (1-D) histogram to decrease the computational complexity. Finally, class mean absolute deviation of each threshold in the 1-D histogram is calculated and the threshold corresponding to the MCMAD is considered as the optimal segmentation threshold. To improve performance, we introduce spectral information into the MCMAD algorithm and the results of spectral bands are combined to get final segmentation results. Because most of the background used in our experiment is vegetation, we introduce a normalized difference vegetation index band into our algorithm and use the MCMAD algorithm on it. Experimental results show that our algorithms not only perform better for remote sensing images but also meet time requirements.

Figures in this Article
© 2014 Society of Photo-Optical Instrumentation Engineers

Citation

Libao Zhang and Aoxue Li
"Thresholding-based remote sensing image segmentation using mean absolute deviation algorithm", J. Appl. Remote Sens. 8(1), 083542 (Oct 27, 2014). ; http://dx.doi.org/10.1117/1.JRS.8.083542


Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

PubMed Articles
Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.