Mallat Fusion for Multi-Source Remote Sensing Classification

The fusion of multi-source remote sensing data is to offer improved accuracies in land cover classification. The conventional fusion methods such as HIS and PCA can not enhance information and simultaneously preserve high fidelity. Thus, the fused image is not preferable for classification. In this paper, the multi-source remote sensing data fusion based on Mallat algorithm for classification is proposed. The purpose of fusion is to create a new image that is more suitable for recognition. The topic focuses on the pyramid decomposition and choosing coefficients in the fusion process. The performance of proposed method is assessed by statistical methods and its effectiveness also testified by classification accuracies