Python Image Processing Projects - Hyperspectral Image Classification - ClickMyProject
Accurate classification of ground features through hyper spectral images is an important research content and has attracted widespread attention. Many methods have achieved good classification results in the classification of hyper spectral images. This paper reviews the classification methods of hyper spectral images from three aspects: supervised classification, semi supervised classification, and unsupervised classification convolutional neural networks are employed to classify hyper spectral images directly in spectral domain These five layers are implemented on each spectral signature to discriminate against others. Experimental results based on several hyper spectral image data sets demonstrate that the proposed method can achieve better classification performance than some traditional methods, such as support vector machines and the conventional deep learning-based methods.
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