Name
Abstract | ||
|---|---|---|
A new method for the segmentation of textured backscattering strength (BS) sonar images is presented. The method is based on the analysis of joint wavelet statistics by using the whole information brought by co- occurrence distributions. After the wavelet transform of the image, on the most informative frequency bands of the wavelet transform, we discriminate between textures by directly measuring the similarity between co-occurrence statistics. Then, we fuse the different segmentations according to the weighted voting rule. Results on real sonar images and textures from the Brodatz album illustrate the effectiveness of the scheme. Finally, performances and results are discussed. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/ICIP.2004.1421397 | Image Processing, 2004. ICIP '04. 2004 International Conference |
Keywords | Field | DocType |
backscatter,geophysical signal processing,image segmentation,image texture,remote sensing,sonar imaging,statistics,wavelet transforms,Brodatz album,cooccurrence statistics,joint wavelet statistics,multiscale segmentation,textured backscattering strength sonar image,wavelet transform | Computer science,Image segmentation,Weighted voting,Sonar,Artificial intelligence,Wavelet,Wavelet transform,Computer vision,Pattern recognition,Image texture,Segmentation,Backscatter,Statistics | Conference |
Volume | ISSN | ISBN |
3 | 1522-4880 | 0-7803-8554-3 |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| I. Karoui | 1 | 22 | 1.91 |
| Jean-Marc Boucher | 2 | 132 | 22.28 |
| Ronan Fablet | 3 | 312 | 47.04 |
| Jean-Marie Augustin | 4 | 42 | 4.20 |