Satellite Image Classification Using K-Means and SVD Techniques
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The motivation of this book is to classify satellite image using the singular value decomposition (SVD) and K-Means techniques. All the proposed methods are consisted of two phases; the enrollment and classification. The enrollment phase aims to extract the image classes to be stored in dataset as a training data. It cannot enroll the intended dataset. The classification phase consisted of multi stages; image composition, image transform, image partitioning, feature extraction, and then image classification. The classification method used the dataset to estimate the classification feature and ...
The motivation of this book is to classify satellite image using the singular value decomposition (SVD) and K-Means techniques. All the proposed methods are consisted of two phases; the enrollment and classification. The enrollment phase aims to extract the image classes to be stored in dataset as a training data. It cannot enroll the intended dataset. The classification phase consisted of multi stages; image composition, image transform, image partitioning, feature extraction, and then image classification. The classification method used the dataset to estimate the classification feature and compute the similarity measure for each block in the image.
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