Image Fusion is used to retrieve important data from a set of input images and put it into a single output image to make it more informative and useful than any of the input images. It improves quality and applicability of data. Quality of the fused image depends on the application. Image fusion is widely used in intelligent robots, stereo camera fusion, medical imaging, and manufacture process monitoring, electronic circuit design and inspection, complex machine/device diagnostics and in intelligent robots on assembly lines. This paper presents a literature review on various spatial and frequency domain image fusion techniques such as averaging, min-max, block replace, HIS,PCA, brovey, pyramid based and transform based techniques. Various quality measures have been discussed to perform quantitative comparison of these methods.

Image fusion is the process of merging multiple images to generate a single image called ‘fused image’ which is more informative than input images in terms of human perception and machine processing. In medical applications, images of the same or different modalities are fused to generate a new image which helps clinicians in reliable and accurate diagnosis. Fused image of mono‐modal medical images is used to see pre‐ and post‐operative results. Multi‐modal medical images are fused for treatment or surgical planning. In this study, the authors have focused on the fusion of lumbar spine images of two completely different modalities: Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). CT provides bony details whereas MR provides soft tissue details. Since the two images are captured using two different machines, these images need to be strictly aligned with each other before fusing. Kekre's Hybrid wavelet transform (KHWT) is used to fuse registered images using combinations of six different orthogonal transforms with four different transform sizes. It is compared with five other fusion methods in qualitative and quantitative ways. The overall comparison indicates that the fused image generated using KHWT is better than input images in terms of content, quality and contrast.

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