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Matching images from different sources.
Looking for information, algorithms, etc. on how to match images of the same object obtained from different sources. (Also on what would be the proper terminology to describe this problem. I'm sure I am doing a poor job here. ) For example, I may take pictures of a cloud formation using three cameras sensible to the visible, infrared and ultraviolet spectra. The cameras, although close to each other, may be located far enough to introduce parallax errors, they may have different resolutions, the images capture may not be simultaneous, so the cloud shapes may change slightly from one image to the next, etc. By 'matching' I mean scaling and rotating the images so that they can be overlaid in such a way that all the data in any area of the screen is coming from the same 'region' in the physical world. The matching process should be based only in the images, I may not have enough information about the cameras physical location and orientation. I understand that in the most general case the images could be so different that this problem is unsolvable, but I still expect to be able to find (partial) solutions when some minimal correlation level exists. Thanks, Roberto Waltman [ Please reply to the group, return address is invalid ] |
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