Wavelet-based image fusion and quality assessment

Recent developments in satellite and sensor technologies have provided high-resolution satellite images. Image fusion techniques can improve the quality, and increase the application of these data. This paper addresses two issues in image fusion (a) the image fusion method and (b) corresponding quality assessment. Firstly, a multi-band wavelet-based image fusion method is presented, which is a further development of the two-band wavelet transformation. This fusion method is then applied to a case study to demonstrate its performance in image fusion. Secondly, quality assessment for fused images is discussed. The objectives of image fusion include enhancing the visibility of the image and improving the spatial resolution and the spectral information of the original images. For assessing quality of an image after fusion, we define the aspects to be assessed initially. These include, for instance, spatial and spectral resolution, quantity of information, visibility, contrast, or details of features of interest. Quality assessment is application dependant; different applications may require different aspects of image quality. Based on this analysis, a set of qualities is classified and analyzed. These sets of qualities include (a) average grey value, for representing intensity of an image, (b) standard deviation, information entropy, profile intensity curve for assessing details of fused images, and (c) bias and correlation coefficient for measuring distortion between the original image and fused image in terms of spectral information.