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A Novel Image Classification Algorithm Using Overcomplete Wavelet Transforms
Abstract— A Novel Image Classification Algorithm Using Overcomplete Wavelet Transforms. A novel frequency-based classification framework and new wavelet algorithm (Wave-CLASS) is proposed using an over complete decomposition procedure. This approach omits the down sampling procedure and produces four-texture information with the same dimension of the original image or window at infinite scale. Three image subsets of Quick Bird data < Final Year Projects 2016 > i.e., park, commercial, and rural over a central region in the city of Phoenix were used to examine the effectiveness of the new wavelet over complete algorithm in comparison with a widely used classical approach (i.e., maximum likelihood). While the maximum-likelihood classifier produced as a 78.29% overall accuracies for all three image subsets.
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