24th Signal Processing and Communication Application Conference (SIU), Zonguldak, Turkey, 16 - 19 May 2016, pp.905-908, (Full Text)
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.