Abstract

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.

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