In this chapter, we discuss image fusion approaches using two edge-preserving filters, namely, guided filter and difference of Gaussians (DoGs). Since the MS and Pan images have high spectral and high spatial resolutions, respectively, one can obtain the resultant fused image using these two images by injecting the missing high frequency details from the Pan image into the MS image. The quality of the final fused image will then depend on the method used for the extraction of high frequency details and also on the technique for injecting those details into the MS image. In the literature on multi-resolution image fusion, various approaches have been proposed based on the aforementioned process that also include state-of-the-art methods such as additive wavelet luminance proportional (AWLP) [178] and generalized Laplacian pyramid-context based decision (GLP-CBD) [13]. Motivated by these works, we first address the fusion problem by using different edge-preserving filters in order to extract the high frequency details from the Pan image. Specifically, we have chosen the guided filter and difference of Gaussians (DoGs) for detail extraction since these are more versatile in applications involving feature extraction, denoising, etc.

Related Work

A large number of techniques have been proposed for the fusion of Pan and MS images, which are based on extracting the high frequency details from the Pan image and injecting them into the MS image. They were discussed in detail in the chapter on literature survey. These methods broadly cover categories such as projection substitution methods, that is, those based on principal component analysis (PCA), intensity hue saturation (IHS) [50, 231], and multi-resolution approaches based on obtaining a scale-by-scale description of the information content of both MS and Pan images [144, 174]. Among these, the multi-resolution based methods have proven to be successful [226]. Most multi-resolution techniques are based on wavelet decomposition [144, 174], in which the MS and Pan images are decomposed into approximation and detail sub-bands; the detail sub-band coefficients of the Pan image are injected into the corresponding sub-band of the MS image by a predefined rule in which the MS image is first interpolated to make it to the size of Pan image.