Volume 9 Number 7 (Jul. 2014)
Home > Archive > 2014 > Volume 9 Number 7 (Jul. 2014) >
JCP 2014 Vol.9(7): 1731-1737 ISSN: 1796-203X
doi: 10.4304/jcp.9.7.1731-1737

A Region Segmentation Algorithm for Remote Sensing Imaging Combined with Multi-feature and Multi-band

Xiaoqing Zuo1, Lei Chen1, Yongchuan Zhang2
1Faculty of Land and Resource Engineering, Kunming University of Science and Technology, Kunming, China
2School of Resource and Environmental Sciences, Wuhan University, Wuhan, China


Abstract—High spatial resolution remote sensing images provide many rich features, such as spectrum, shape, texture, etc. However, only spectral character is adopted in many traditional image segmentation methods, leading to segmentation results unsatisfactory. A multi-feature and multi-band region segmentation algorithm (MM-RSA) is proposed. First, texture image of a band is extracted and is combined into multi-spectral image. Second, seed region is selected from the combined multi-spectral image using Fuzzy C-Means Clustering method. Third, the segmentation process is performed by employing a region growing criterion, which integrates spectral and shape feature information. The algorithm not only integrates the criterions of spectrum, texture and shape, but also is of multi-scale characteristic. Experiments were conducted on a QuickBird image to evaluate the performance, and the results showed that the MM-RSA is able to effectively obtain segmentation results at different scales, and the overall performance of segmentation is improved when compared with pixel-based segmentation algorithm and multi-resolution-based segmentation algorithm.

Index Terms—multi-feature, multi-band, multi-scale, region segmentation, remote sensing image

[PDF]

Cite: Xiaoqing Zuo, Lei Chen, Yongchuan Zhang, "A Region Segmentation Algorithm for Remote Sensing Imaging Combined with Multi-feature and Multi-band," Journal of Computers vol. 9, no. 7, pp. 1731-1737, 2014.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat,etc
E-mail: jcp@iap.org
  • Nov 14, 2019 News!

    Vol 14, No 11 has been published with online version   [Click]

  • Mar 20, 2020 News!

    Vol 15, No 2 has been published with online version   [Click]

  • Dec 16, 2019 News!

    Vol 14, No 12 has been published with online version   [Click]

  • Sep 16, 2019 News!

    Vol 14, No 9 has been published with online version   [Click]

  • Aug 16, 2019 News!

    Vol 14, No 8 has been published with online version   [Click]

  • Read more>>