A new wavelet‐based image fusion method for remotely sensed data

Abstract

The preservation of spectral characteristics and the retention of high spatial resolution are two key issues in image fusion. Different applications may require different balances between the two. However, the limitation is that only one fused result is possible for most of the commonly used fusion methods; users have no control over how much spatial detail or spectral information should be retained. Both quantitative and qualitative criteria, including mean, standard deviation, entropy, average gradient, spectral distortion, correlation coefficient and visual assessment, were used to evaluate the performance of the proposed fuser. A SPOT (Satellite Pour l'Observation de la Terre) panchromatic image and Landsat Thematic Mapper (TM) images were employed in the evaluation. The results show that the proposed method is slightly better than, or comparable to, commonly used image fusion methods, including Intensity–Hue–Saturation (IHS), principal component analysis (PCA), and two other wavelet‐based fusion methods with replacement and with selection strategies, in terms of spectral characteristic preservation and high spatial resolution retention. Moreover, the proposed method can achieve a wide range of balances between spectral characteristic preservation and high spatial resolution retention, and thus is applicable in different applications.