By Topic

Segmentation algorithm of high resolution remote sensing images based on LBP and statistical region merging

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Luo Bo ; Sch. of Electron. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China ; Cheng Jian

Remote sensing image segmentation is the basis of object-oriented classification of remote sensing images. It is important for the application of remote sensing images. High-resolution remote sensing images contain rich spatial texture information. SRM is an efficient image segmentation algorithm. This paper presents a segmentation algorithm to take full advantage of the high-resolution remote sensing image texture information based on LBP and SRM, in the process of merging, according to the characteristics of regions, select the appropriate method to merge. It works well in the segmentation of high-resolution remote sensing images.

Published in:

Audio, Language and Image Processing (ICALIP), 2012 International Conference on

Date of Conference:

16-18 July 2012