A Comparative Study of various Image fusion Technics

Image fusion refers the process of combining multiple images of a scene to obtain a single composite image. The composite image should contain a more useful description of the scene than provided by any of the individual source images. 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. Here we have consider some image fusion techniques such as averaging, min-max, PCA, brovey, pyramid based and transform based techniques. Various parameters have been considered and varied for all these techniques and found that every algorithm has some advantages and drawbacks. Combination of qualitative and quantitative assessment approach may be the correct way to find out which fusion algorithm is most appropriate for an application.