Title :
Sequence Similarity and Multi-Date Image Segmentation
Author :
Ketterlin, Alain ; Gancarski, Pierre
Author_Institution :
Univ. Louis Pasteur, Strasbourg
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;
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
DOI :
10.1109/MULTITEMP.2007.4293034