Evaluation of Satellite Image Fusion Using Wavelet Transform

This paper addresses the principles, implementation and evaluation of wavelet transformation based image fusion. 2-D discrete wavelet transformation is presented concisely to facility the understanding of the wavelet based image fusion method. To best retain the quality of the input images, we propose a strategy that minimizes the necessary resampling operations to limit potential image quality deterioration. In the proposed fusion approach, the wavelet coefficients for the fused images are selected based on the suggested maximum magnitude criterion. To evaluate the outcome images, other popular fusion methods including principal component transformation, Brovey and multiplicative transformation approaches are applied to the same images and the results are compared to the ones from the wavelet based approach. Fusion results are evaluated both visually and numerically. A quality matrix is calculated based on the correlation coefficients between the fused image and the original image. It is shown that this quality measure can indicate the information content of the fused image comparing to the input panchromatic and multispectral images. Our results clearly suggest that the wavelet based fusion can yield superior properties to other existing methods in terms of both spatial and spectral resolutions, and their visual appearance. This study is carried out using multiple images over the Davis-Purdue Agricultural Center (DPAC) and its vicinity with both urban and rural features. Images used include QuickBird panchromatic band (0.7 m) and multispectral bands (2.7m), and Ikonos panchromatic (1 m) and multispectral bands (4 m).