À Trous Wavelet Decomposition Based Hyperspectral Image Classification

In this study, a new approach is described in hyperspectral remote sensing image classification problem. In this approach, each band of hyperspectral image is decomposed to details by using à trous wavelet decomposition method. The obtained details are injected to the related hyperspectral band additively and proportionally. Thus, the hyperspectral image de- tails are improved. The resulting new image after dimensionality reduction is trained and classified with conventional classifiers and ensemble methods, and their performance is discussed. It has been proven that the proposed method improves the metric results in terms of the overall accuracy and Kappa.