IEEE Transactions on Geoscience and Remote Sensing · 1998 · 160 citations · 12 references
ComputingEarth SciencesGeoinformaticsDigital ImagingImage InterpretationRemote SensingImage ClassificationImage TextureLand Cover MappingRemote Sensing Image AnalysisRemote Sensing ImageryTexture AnalysisClassification AccuracyClassification Accuracy AnalysisClassification Accuracy AssessmentImage Texture AnalysisRemote Sensing ClassificationRemote Sensing Image ClassificationSatellite Image ClassificationSemivariogram
Semivariogram functions are compared to co-occurrence matrices for classification of digital image texture, and accuracy is assessed using test sites. Images acquired over the following six different spectral bands are used: 1) SPOT HRV, near infrared; 2) Landsat thematic mapper (TM), visible red; 3) India Remote Sensing (IRS) LISS-II, visible green; 4) Magellan, Venus, S-band microwave; 5) shuttle imaging radar (SIR)-C, X-band microwave; 6) SIR-C, L-band microwave. The semivariogram textural measure provides a larger classification accuracy than a classifier based on a co-occurrence matrix for the microwave images and a smaller classification accuracy for the optical images.
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Image analysis and mathematical morphology
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Statistical and structural approaches to texture
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