DocumentCode :
2133584
Title :
SAR images filtering and segmentation: a multiresolution and contextual approach
Author :
Franco, J.A. ; Moctezuma, M. ; Barilla, M.E. ; Escalante, B. ; Parmiggiani, F.
Author_Institution :
Graduate Div., Nat. Univ. of Mexico, Mexico
Volume :
5
fYear :
2001
fDate :
2001
Firstpage :
2304
Abstract :
In this work we present a mixed contextual algorithm for segmenting SAR-ERS 1 images (© ESA). The first step was to pre-process the original SAR image by means of a polynomial transform based filter in order to decrease the effect of speckle. Segmentation stage was performed as follows: cluster centers were obtained using a non-contextual algorithm; then, based on a Bayes classifier we achieved a first segmentation step, but defining a ´reject class´; finally, rejected pixels were e-classed via a Markovian model. Results obtained show segmented images exhibiting homogeneous regions and a minimal presence of isolated pixels. As well, they evidence that combined use of polynomial transform and Markov random field theory does not introduce a noticeable degradation of edges in segmented regions
Keywords :
Bayes methods; Markov processes; digital filters; edge detection; image classification; image resolution; image segmentation; polynomials; radar imaging; radar resolution; remote sensing by radar; spaceborne radar; synthetic aperture radar; transforms; Bayes classifier; Markov random field theory; Markovian model; SAR images filtering; SAR-ERS 1 images; cluster centres; contextual approach; degradation; edges; multiresolution approach; noncontextual algorithm; polynomial transform based filter; reject class; rejected pixels; segmentation; Clustering algorithms; Degradation; Filtering; Filters; Image resolution; Image segmentation; Markov random fields; Pixel; Polynomials; Speckle;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001 International
Conference_Location :
Sydney, NSW
Print_ISBN :
0-7803-7031-7
Type :
conf
DOI :
10.1109/IGARSS.2001.977983
Filename :
977983
Link To Document :
بازگشت