HIGH RESOLUTION IMAGE CLASSIFICATION | Zendy

Wasfi Taher Saalih | Zendy

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HIGH RESOLUTION IMAGE CLASSIFICATION

Author(s) -

Wasfi Taher Saalih

Publication year - 2005

Publication title -

iraqi journal of statistical sciences

Language(s) - English

Resource type - Journals

eISSN - 2664-2956

pISSN - 1680-855X

DOI - 10.33899/stats.2005.32857

Subject(s) - linear discriminant analysis , pattern recognition (psychology) , artificial intelligence , discriminant , artificial neural network , computer science , contextual image classification , k nearest neighbors algorithm , field (mathematics) , image (mathematics) , geography , data mining , mathematics , pure mathematics

Classification is an important field with many applications. In particular, the classification of digital imagery has important applications in the mapping community. In this paper the comparison of three different classification methods on LANDSAT imagery of Erbil City IRAQ: neural networks, nearest-neighbor, and discriminant analysis are made. Out of the three approaches, k-nearest neighbors performed the best; next in accuracy was neural networks, and then discriminant analysis.

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