A Probabilistic Method for the Classification of Hyperspectral Images - Kutluk, Sezer; Kayabol, Koray; Akan, Aydin (IEEE, 2016)
In this study a supervised classification and dimensionality reduction method for hyperspectral images is proposed. For this purpose, using probabilistic principal component analysis (PPCA), dimensionality reduction is performed and a Gaussian mixture model (GMM) is built. Alongside this mixture model, spatial information is also included into the classification process by taking advantage of pixel neighborhoods.
24th Signal Processing and Communication Application Conference (SIU) -- MAY 16-19, 2016 -- Zonguldak, TURKEY
Keywords: hyperspectral image; probabilistic principal component analysis; dimensionality reduction; mixture models