Supervised Classification and Unsupervised Classification

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Class Project Report: Supervised Classification and Unsupervised Classification1ATS 670 Class ProjectSupervised Classification and Unsupervised ClassificationXiong LiuAbstract: This project use migrating means clustering unsupervisedclassification (MMC), maximum likelihood Classification (MLC) trained by pickedtraining samples and trained by the results of Unsupervised Classification (HybridClassification) to classify a 512 pixels by 512 lines NOAA-14 AVHRR Local AreaCoverage (LAC) image. All the channels including ch3 and ch3t are used in thisproject.

some clustering algorithm to classify an image data [Richards, 1993, p8 5]. These procedures can be used to determine the number and location of the unimodal spectral classes. One of the most commonly used unsupervised classifications is the migrating means clustering classifier (MMC). This method is based on labeling each

  Classification, Supervised, Spectral, Unsupervised, Clustering, Supervised classification and unsupervised classification