DocumentCode
3297032
Title
Sequence Similarity and Multi-Date Image Segmentation
Author
Ketterlin, Alain ; Gancarski, Pierre
Author_Institution
Univ. Louis Pasteur, Strasbourg
fYear
2007
fDate
18-20 July 2007
Firstpage
1
Lastpage
4
Abstract
Multi-date images present new challenges and new opportunities for image analysis. This paper considers the task of segmenting a multi-date image by clustering its pixels without requiring perfect time-based alignment. It first introduces the problem, and then proceeds with the definition of a similarity measure between sequences of observations, i.e., pixels. This is followed by an explanation of how to use this similarity measure to apply well known clustering algorithms. The paper concludes by some brief experiment descriptions.
Keywords
data analysis; image segmentation; pattern clustering; remote sensing; clustering algorithms; image analysis; multidate image segmentation; pixels clustering; sequence similarity; Clustering algorithms; Data analysis; Image segmentation; Image sensors; Image sequence analysis; Pixel; Sensor phenomena and characterization; Time measurement; Tin; Wavelength measurement;
fLanguage
English
Publisher
ieee
Conference_Titel
Analysis of Multi-temporal Remote Sensing Images, 2007. MultiTemp 2007. International Workshop on the
Conference_Location
Leuven
Print_ISBN
1-4244-0845-8
Electronic_ISBN
1-4244-0846-6
Type
conf
DOI
10.1109/MULTITEMP.2007.4293034
Filename
4293034
Link To Document