Temporal Updating Scheme for Probabilistic Neural Network With Application to Satelite Cloud Classification - Further Results  

Oleh:

Reinke, Donald ; Haar, Thomas H. von der ; Azimi-Sadjadi, M. R. ; Gao, Wenfeng ; Vonder Haar, T. H. ; Reinke, D.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 12 no. 5 (2001), page 1196-1203.
Topik: SATELITE; updating; scheme; probabilistic; neural networks; satelite cloud; classification

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.5 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

A novel temporal updating approach for probabilistic neural network classifiers was developed by Tian et al. (2000) to account for temporal changes of spectral and temperature features of clouds in the visible and infrared GOES 8 (Geostationary Operational Environmental Satellite) imagery data. In this paper, a new method referred to as moving singular value decomposition (MSVD) is introduced to improve the classification rate of the boundary blocks or blocks containing cloud types with non-uniform texture. The MSVD method is then incorporated into the temporal updating scheme and its effectiveness is demonstrated on several sequences of GOES 8 cloud imagery data. These results indicate that the incorporation of the new MSVD improves the overall performance of the temporal updating process by almost 10 %.

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