Efficient texture analysis of SAR imagery
| Autor: | Donald A. Adjeroh, Moon-Chuen Lee, Umasankar Kandaswamy |
|---|---|
| Rok vydání: | 2005 |
| Předmět: |
Synthetic aperture radar
Contextual image classification business.industry Computer science Feature extraction Gabor wavelet ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Texture (geology) Matrix (mathematics) ComputingMethodologies_PATTERNRECOGNITION Image texture Radar imaging General Earth and Planetary Sciences Computer vision Artificial intelligence Electrical and Electronic Engineering business ComputingMethodologies_COMPUTERGRAPHICS |
| Zdroj: | IEEE Transactions on Geoscience and Remote Sensing. 43:2075-2083 |
| ISSN: | 0196-2892 |
| DOI: | 10.1109/tgrs.2005.852768 |
| Popis: | We address the problem of efficiency in texture analysis for synthetic aperture radar (SAR) imagery. Motivated by the statistical occupancy model, we introduce the notion of patch reoccurrences. Using the reoccurrences, we propose the use of approximate textural features in analysis of SAR images. We describe how the proposed approximate features can be extracted for two popular texture analysis methods-the gray-level cooccurrence matrix and Gabor wavelets. Results on image texture classification show that the proposed method can provide an improved efficiency in the analysis of SAR imagery, without introducing any significant degradation in the classification results. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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