Title :
A new region growing-based segmentation method for high resolution remote sensing imagery
Author :
Xiuxia Li;Linhai Jing;Qizhong Lin;Hui Li;Ru Xu;Yunwei Tang;Haifeng Ding;Qingjie Liu
Author_Institution :
Key Laboratory of Digital Earth, Institute of Remote Sensing, and Digital Earth, Chinese Academy of Sciences, Beijing, China, 100094
fDate :
7/1/2015 12:00:00 AM
Abstract :
In this article, a newsegmentation method based on traditional region growing (RG) is proposed for high resolutionremote sensing imagery. This method takes regional minima from horizontal and vertical gradient maps of the image as seeds for the following region growing processing. The new method consists of several steps as follows: (1)deriving a morphological gradient map from the input multispectral image, (2) morphologically filtering the gradient image to remove local minima with small depthand extracting regional minima of flat areas in the resulting filtered image as seeds, (3) segmenting the multispectral image using the RG approach with reference to the seeds, and (4) merge the resulting initial segments to yield asegmentation map. In a test with a WorldView-2 multispectral image, the proposed method offered segmentation maps with nearly the same accuracy as several current methods.
Keywords :
"Image segmentation","Remote sensing","Spatial resolution","Merging","Sensors","Indexes"
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International
Electronic_ISBN :
2153-7003
DOI :
10.1109/IGARSS.2015.7326784