Comparison of fuzzy c-means classification, linear mixture modelling and MLC probabilities as tools for unmixing coarse pixels

Keyphrases

• Fuzzy C-means 100%
• Land Cover 100%
• Fuzzy C-Means Segmentation 100%
• Linear Mixture Modeling 100%
• Maximum Likelihood Classification 100%
• Unmixing 100%
• Linear Mixture Model 100%
• Probability Value 50%
• Asymmetric Filter 50%
• Model Value 50%
• Best Prediction 50%
• Sub-pixel 50%
• Mean Filter 50%
• Thematic Mapper 50%
• Supervised Classification 50%
• Fractional Maps 50%
• Sensor Sampling 50%
• Soft Classifier 50%
• Mixture of Probability Distributions 50%
• Multispectral Scanner 50%
• Filter Kernel 50%
• Hard Classification 50%

Computer Science

• fuzzy c mean 100%
• Linear Mixture 100%
• unmixing 100%
• maximum-likelihood 66%
• Supervised Classification 33%
• Probability Value 33%

Mathematics

• Probability Theory 100%
• Mixture Model 100%
• Maximum Likelihood 100%
• Asymmetric 50%
• Probability Value 50%