Using a Wavelet Based Method for High Resolution Satellite Image Fusion

Abstract

The number and quality of commercially available multispectral sensors and the data they provide are continually improving, but there is always compromise between achieving high spatial resolution, necessary for those applications that require high degree of detail, and high spectral resolution when a better feature discrimination level is needed. However, there are some situations that simultaneously require high spatial and spectral resolutions in a single image. The techniques of data fusion, or data merging, provide an alternative to that constraint, being used to combine low-resolution multispectral satellite imagery with higher resolution panchromatic or radar imagery, improving their visual quality and interpretability. Many algorithms and software tools have been developed for fusing panchromatic and multispectral datasets in remote sensing. Wavelet techniques are increasingly being used for the processing of images. The algorithm used in this paper was based on multiresolution wavelet decomposition. The image is decomposed into multiple channels based on their local frequency content, obtaining new images each one of them with different degree of resolution. A simple Wavelet Transform is used, which is implemented in the ERDAS Imagine Software package ver. 9.2. The procedure was based upon the wavelet transform is to improve the spectral quality of high resolution image acquired by LANDSAT 7 ETM+. Keywords: image fusion, merging, wavelets, multiresolution.