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Showing 1 to 9 of 9 for “"ISODATA"”.

  1. Integrating spatial and spectral information for automatic feature identification in high -resolution remotely sensed images

    … methods were compared: the pixel-based ISODATA and maximum likelihood approaches, field-based ECHO, and region based maximum likelihood using patch means, a divergence index, and patch probability density functions (pdfs). Classification with the divergence index showed the lowest …

    wvu Repository record for Integrating spatial and spectral information for automatic feature identification in high -resolution remotely sensed images (opens in a new tab)

  2. Colour analysis and the classification of fruit

    … methods of the K-means algorithm and the ISODATA classification approach. The ICS Texicon computer spectrophotometer (ICS Texicon Spectraflash Manual (1991)) was used to check the performance of most of the colour systems described by analyzing apple sample colours

    cape-town Repository record for Colour analysis and the classification of fruit (opens in a new tab)

  3. Comparison of accuracy and efficiency of five digital image classification algorithms

    … technique with a spatial constraint) b) ISODATA (a hybrid minimum distance classifier) c) BOXDEC (a discrete parallelepiped classifier) d) BCLAS (a Bayesian classifier) e) HYPBOX (a combined parallelepiped-Bayesian classifier) Two sets of training data, developed for each study site were …

    vt Repository record for Comparison of accuracy and efficiency of five digital image classification algorithms (opens in a new tab)

  4. Spectral Identification of Wild Rice (Zizania palustris L.) Using Indigenous Knowledge and Landsat Multispectral Data

    … factor. Masking upland areas using a 5-category ISODATA Boolean mask improved the classification results of the aquatic emergent vegetation. Maximum likelihood classification yielded a 79.03% accuracy (kappa = 0.6747) and a minimum distance to means classification yielded a 51.61% accuracy (kappa …

    montana-tech Repository record for Spectral Identification of Wild Rice (Zizania palustris L.) Using Indigenous Knowledge and Landsat Multispectral Data (opens in a new tab)

  5. Spectral Identification of Wild Rice (Zizania palustris L.) Using Indigenous Knowledge and Landsat Multispectral Data

    … factor. Masking upland areas using a 5-category ISODATA Boolean mask improved the classification results of the aquatic emergent vegetation. Maximum likelihood classification yielded a 79.03% accuracy (kappa = 0.6747) and a minimum distance to means classification yielded a 51.61% accuracy (kappa …

    montana Repository record for Spectral Identification of Wild Rice (Zizania palustris L.) Using Indigenous Knowledge and Landsat Multispectral Data (opens in a new tab)

  6. The influence of snowcover distribution and variable melt regimes on the transport of nutrients from two high Arctic watersheds

    … was applied to the two watersheds using an ISODATA unsupervised classification scheme to determine watershed SWE. The terrain model confirmed that topography likely explains greater SWE in the West watershed, and provides a method for reproducible estimates of watershed SWE in future years. …

    queens Repository record for The influence of snowcover distribution and variable melt regimes on the transport of nutrients from two high Arctic watersheds (opens in a new tab)

  7. Quantifying Atherosclerosis: IVUS Imaging For Lumen Border Detection And Plaque Characterization

    … At the bottom of decomposition tree, we employed ISODATA to cluster enveloped detected features in an unsupervised fashion and classify atherosclerotic plaque constitutes into fibrotic, lipidic, calcified, and no tissues. For the first time, we studied numbers of factors that were necessary for …

    columbia-diss Repository record for Quantifying Atherosclerosis: IVUS Imaging For Lumen Border Detection And Plaque Characterization (opens in a new tab)

  8. Ocean-surface heterogeneity mapping: exploiting hypertemporal datasets in support of seascape ecology research

    … MApping (OHMA) algorithm uses unsupervised ISODATA clustering, an ensemble approach, and a data-driven optimisation process, to identify where boundaries between different ocean regions frequently occur. OHMA effectively produces a suite of complementary datasets – a single STH image dataset …

    cork Repository record for Ocean-surface heterogeneity mapping: exploiting hypertemporal datasets in support of seascape ecology research (opens in a new tab)