A Parallel Fusion Algorithm of Remote Sensing Images Based on Wavelet Transform

To play the advantages of a variety of remote sensing data, the application of remote sensing image fusion is a very important choice. Remote sensing image fusion is large in computing capacity and time-consuming, and with the development of modern remote sensing technology, the amount of various remote sensing data obtained is larger and larger, how to fuse remote sensing image quickly and accurately and getting useful information is becoming more and more urgent especially in some remote sensing applications such as disaster prevention and relief quick, etc. Based on the advantage of wavelet transform in information processing and the advantage of parallel computing in high-performance computing, a parallel fusion algorithm of remote sensing images based on wavelet transform is proposed in the paper. In the method, based on parallel computing, the low-frequency components of wavelet decomposition are fused with the fusion rule based on the feature matching, and the high-frequency components of wavelet decomposition are fused with the fusion rule based on the sub region variance. Then the low-frequency components and the high-frequency components after fusion are processing with the inverse wavelet transform, and the fused image is gotten. The result shows that the proposed method can get better fusion results and faster computing speed.