Remote sensing image segmentation using RPCCL and labeling watershed transform

Xinhui Li; Renxi Chen

doi:10.1117/12.833691

30 October 2009 Remote sensing image segmentation using RPCCL and labeling watershed transform

Xinhui Li, Renxi Chen

Proceedings Volume 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications; 74981X (2009) https://doi.org/10.1117/12.833691
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

Image segmentation is the technology that separating the image into several characteristic areas and is very important to image analysis. In this paper, we propose a new segmentation method based on rival penalized controlled competitive learning (RPCCL) and watershed transform. We apply watershed transform and RPCCL clustering algorithm separately on input image, and then combine the two results of them. Compared to traditional watershed segmentation, our method can avoid over-segmentation and obtain better results.

Citation Download Citation

Xinhui Li and Renxi Chen "Remote sensing image segmentation using RPCCL and labeling watershed transform", Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 74981X (30 October 2009); https://doi.org/10.1117/12.833691

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available