Pixel- and region-based image fusion with complex wavelets

A number of pixel-based image fusion algorithms (using averaging, contrast pyramids, the discrete wavelet transform and the dual-tree complex wavelet transform (DT-CWT) to perform fusion) are reviewed and compared with a novel region-based image fusion method which facilitates increased flexibility with the definition of a variety of fusion rules. A DT-CWT is used to segment the features of the input images, either jointly or separately, to produce a region map. Characteristics of each region are calculated and a region-based approach is used to fuse the images, region-by-region, in the wavelet domain. This method gives results comparable to the pixel-based fusion methods as shown using a number of metrics. Despite an increase in complexity, region-based methods have a number of advantages over pixel-based methods. These include: the ability to use more intelligent semantic fusion rules; and for regions with certain properties to be attenuated or accentuated.A number of pixel-based image fusion algorithms (using averaging, contrast pyramids, the discrete wavelet transform and the dual-tree complex wavelet transform (DT-CWT) to perform fusion) are reviewed and compared with a novel region-based image fusion method which facilitates increased flexibility with the definition of a variety of fusion rules. A DT-CWT is used to segment the features of the input images, either jointly or separately, to produce a region map. Characteristics of each region are calculated and a region-based approach is used to fuse the images, region-by-region, in the wavelet domain. This method gives results comparable to the pixel-based fusion methods as shown using a number of metrics. Despite an increase in complexity, region-based methods have a number of advantages over pixel-based methods. These include: the ability to use more intelligent semantic fusion rules; and for regions with certain properties to be attenuated or accentuated