Utilisation of contour criteria in micro-segmentation of SAR images

@article{Beaulieu2004UtilisationOC,
  title={Utilisation of contour criteria in micro-segmentation of SAR images},
  author={Jean-Marie Beaulieu},
  journal={International Journal of Remote Sensing},
  year={2004},
  volume={25},
  pages={3497 - 3512}
}
  • Jean-Marie Beaulieu
  • Published 1 September 2004
  • Environmental Science
  • International Journal of Remote Sensing
The segmentation of SAR (Synthetic Aperture Radar) images is greatly complicated by the presence of coherent speckle. To carry out this process a hierarchical segmentation algorithm based on stepwise optimization is used. It starts with each individual pixel as a segment and then sequentially merges the segment pair that minimizes the criterion. In a hypothesis testing approach, we show how the stepwise merging criterion is derived from the probability model of image regions. The Ward criterion… 
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10 Citations
Highly Influential Citations
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Background Citations
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Methods Citations
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10 Citations

Pseudo-convex Contour Criterion for Hierarchical Segmentation of SAR Images

  • Jean-Marie Beaulieu
  • Mathematics
    The 3rd Canadian Conference on Computer and Robot Vision (CRV'06)
  • 2006
In this paper, it is examined how the pseudo-convex envelope of a region can be used to evaluate the region contour and a pseudo- Convex measure adapted to the geometry of image lattice is presented.

Segmentation of Polarimetric Sar Images Composed of Textured and Non-Textured Fields

Segmentation of polarimetric SAR image is a difficult problem. We show that image segmentation can be viewed as a likelihood approximation problem. The optimum criterion is derived for a hierarchical…

Segmentation of textured polarimetric SAR scenes by likelihood approximation

It is shown that image segmentation can be viewed as a likelihood approximation problem and a field-adaptable segmentation strategy combining different criteria is examined.

Segmentation, regroupement et classification pour l'analyse d'image polarimétrique radar

The objective of the thesis is to show and illustrate the advantages of the hierarchical segmentation and clustering for the analysis of polarimetric radar images and improve the results of H/A/alpha classification and Wishart clustering.

An Adaptive Technique based on Similarity Measures for Change Detection in Very High Resolution SAR Images

  • F. BovoloL. Bruzzone
  • Environmental Science, Mathematics
    IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium
  • 2008
This paper presents a novel adaptive technique for change detection in very high geometrical resolution (VHR) Synthetic Aperture Radar (SAR) images that exploits information theoretical similarity…

An approach to change detection in time series of SAR images based on multitemporal similarity measures

This work deals with a novel adaptive parcel-based method for change detection in long time series of SAR images. The proposed technique considers two temporal series of SAR images acquired over the…

Développement d'outils et de méthodes de télédétection spatiale optique et radar nécessaires à la haute résolution spatiale

En utilisant le modele multiplicatif scalaire, nous derivons l'expression litterale de the distribution de the matrice de coherence et nous proposons d'implementer cette nouvelle distribution dans un algorithme de segmentation hierarchique.

Hierarchical segmentation of polarimetric SAR images

A hierarchical stepwise optimization process is used for polarimetric SAR image segmentation and the proposed criterion is based upon the testing of the equality of covariance matrices of adjacent regions.

A novel multi-scale level set method for SAR image segmentation based on a statistical model

A novel threshold segmentation result is used to represent the initial segmentation curve and an improved multi-layer approach is introduced for multi-region segmentation based on the multi-scale level set framework.

Segmentation of textured scenes using polarimetric SARs

  • Jean-Marie BeaulieuR. Touzi
  • Environmental Science, Mathematics
    IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477)
  • 2003
It is shown that image segmentation can be viewed as a likelihood approximation problem and the optimum criterion is derived for segmentation of K-distributed textured polarimetric SAR images.

References

SHOWING 1-10 OF 26 REFERENCES

Quantitative comparison of the performance of SAR segmentation algorithms

On real data, MAP estimation was markedly the better method and retained performance comparable to that on simulated data, while the performance of the other algorithm deteriorated sharply.

An optimal multiedge detector for SAR image segmentation

A new step-edge detector for SAR images is proposed, which is optimal in the minimum mean square error (MSSE) sense under a stochastic multiedge model and thresholding of the edge strength map by a modified version of the watershed algorithm and region merging to eliminate false edges complete an efficient segmentation scheme.

Watershed-based hierarchical SAR image segmentation

Watershed transformation is a powerful image segmentation tool recently developed in mathematical morphology. In order to segment images initially oversegmented by watershed transformation, two…

Segmentation of radar imagery using the Gaussian Markov random field model

Segmentation of highly speckled radar imagery is achieved by the use of the Gaussian Markov random field model. The model considers two regions to be different if one or more than one of the…

Refining image segmentation by integration of edge and region data

To find the ideal segmentation, the authors develop a stopping criterion for their Iterative Parallel Region Growing (IPRG) algorithm using additional information from edge features, and the Hausdorff distance metric.

An automated region growing algorithm for segmentation of texture regions in SAR images

Synthetic Aperture Radar (SAR) images have a high geomorphologic information content. Due to the particular operation of this sensor the geomorphologic features of the Earth's surface are enhanced,…

Segmentation of textured images using a multiresolution Gaussian autoregressive model

A new algorithm for segmentation of textured images using a multiresolution Bayesian approach which is a natural extension of the single-resolution "maximization of the posterior marginals" (MPM) estimate.

Speckle reduction and segmentation of Synthetic Aperture Radar images

A fully automatic, unsupervised segmentation algorithm, based on the iterative application of the new filter, is described and successfully applied to ERS-1 Synthetic Aperture Radar (SAR) images of sea ice.

A multiresolution image segmentation technique based on pyramidal segmentation and fuzzy clustering

An unsupervised image segmentation technique is presented, which combines pyramidal images segmentation with the fuzzy c-means clustering algorithm, which shows good performance in detecting LV lumen in MR images.

Adaptation of the Hierarchical Stepwise Segmentation Algorithm for automatic segmentation of a SAR mosaic

An efficient procedure which can be used to segment and classify large zones of the CAMP (Central Africa Mosaic Project) radar image mosaic in tropical forest regions is obtained.