Multispectral and SAR image fusion with a multiresolution directional-oriented image transform based on Gaussian derivatives

摘要

In this paper, we present two novel methodologies for image-fusion. First we fuse multispectral images from the same satellite (Landsat ETM+) with different spatial resolutions. In this case we show how the proposed method can help improve spatial resolution. In the second case, we fuse multispectral Landsat ETM+ and SAR images combining with a speckle reduction method for the latter. Both algorithms are based on a Gaussian-derivative image transform. This is a multi-channel model for image representation based on the scale-space theory. Moreover, locally rotating the image transform allows better edge reconstruction and restoration from noise. We show that multispectral image fusion with the Hermite Transform preserves the biophysical variable interpretation of the original images.