Methods of image segmentation become more and more important in the field of remote sensing image analysis – in particular due to the increasing spatial resolution of imagery. The most important factor for using segmentation techniques is segmentation quality. Thus, a method for evaluating segmentation quality is presented and used to compare results of presently available segmentation programs. Firstly, an overview of the softwares used is given. Moreover the quality of the individual segmentation results is evaluated based on pan-sharpened multi-spectral IKONOS data. This is done by visual comparison, which is supplemented by a detailed investigation using visual interpreted reference areas. Geometrical segment properties are in the focus of this quantitative evaluation. The results are assessed and discussed. They show the suitability of the tested programs for segmenting very high resolution imagery. KURZFASSUNG: Die Methoden der Bildsegmentierung gewinnen in der Fernerkundung – insbesondere durch die steigende geometrische Auflosung der Bilddaten – zunehmend an Bedeutung. Vor diesem Hintergrund wird die Segmentierungsqualitat derzeit verfugbarer Segmentierungssoftwares gegenubergestellt. Dabei erfolgt zunachst eine allgemeine Darstellung der benutzten Programme. Anschliesend wird die Qualitat der auf Basis panchromatisch gescharfter IKONOS-Multispektraldaten erzielten Segmentierungsergebnisse verglichen. Eine uberblicksartige visuelle Untersuchung wird um einen detaillierten Vergleich mit unterschiedlichen, visuell kartierten Referenzflachen erganzt. Grose Beachtung finden die fur die Segmentierungsqualitat ausschlaggebenden geometrischen Eigenschaften der Segmente. Die unterschiedlichen Ergebnisse werden bewertet und diskutiert. Sie dokumentieren die Eignung der Programme zur Segmentierung sehr hochauflosender Fernerkundungsdaten.
[1]
M. Neubert,et al.
THE POTENTIAL USE OF VERY HIGH RESOLUTION SATELLITE DATA FOR URBAN AREAS – FIRST EXPERIENCES WITH IKONOS DATA, THEIR CLASSIFICATION AND APPLICATION IN URBAN PLANNING AND ENVIRONMENTAL MONITORING
,
2001
.
[2]
Arno Schäpe,et al.
Multiresolution Segmentation : an optimization approach for high quality multi-scale image segmentation
,
2000
.
[3]
Sankar K. Pal,et al.
A review on image segmentation techniques
,
1993,
Pattern Recognit..
[4]
R. Kettig,et al.
Classification of Multispectral Image Data by Extraction and Classification of Homogeneous Objects
,
1976,
IEEE Transactions on Geoscience Electronics.
[5]
D. Maktav,et al.
Remote sensing of urban areas
,
2005
.
[6]
Linda G. Shapiro,et al.
Image Segmentation Techniques
,
1984,
Other Conferences.
[7]
Rod Cook,et al.
Segmentation and simulated annealing
,
1996,
Remote Sensing.
[8]
F. Wörgötter,et al.
Cluster update algorithm and recognition
,
2000
.
[9]
Joachim M. Buhmann,et al.
A New Adaptive Algorithm for the Polygonization of Noisy Imagery
,
2001
.