Segmentation algorithm of high resolution remote sensing images based on LBP and statistical region merging
- Resource Type
- Conference
- Authors
- Bo, Luo; Jian, Cheng
- Source
- 2012 International Conference on Audio, Language and Image Processing Audio, Language and Image Processing (ICALIP), 2012 International Conference on. :337-341 Jul, 2012
- Subject
- Signal Processing and Analysis
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Image segmentation
Remote sensing
Merging
Classification algorithms
Algorithm design and analysis
Spatial resolution
- Language
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.