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I am attempting to combine two radar images, each of which is a 3-dimensional cube with a range dimension, an azimuth angle dimension, and an elevation angle dimension. One image has high azimuth resolution but low elevation resolution, while the other has high elevation resolution but low azimuth resolution.

Is there an effective way to combine these images to create a single image, and what sort of resolution can I achieve with the new image?

Thank you in advance for any advice or resources.

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  • $\begingroup$ So you have two different images of the same scene ? How different are they? Only resolutions ? And effective means: accurate, or efficient, or practical ? $\endgroup$ – Fat32 Sep 30 at 22:02
  • $\begingroup$ Two images of the same scene, yes. Only the resolutions should be different. I'm starting with a proof of concept, so accurate first, then I'll work on efficient and practical later. $\endgroup$ – Sean Holloway Sep 30 at 22:19
  • $\begingroup$ So what you are looking for is some sort of a reconstruction algorithm. If you think your 'images' have x, y, z coordinates, your first image has a high resolution in x-y where the second one has high resolution in y-z. Start with y and use a matching algorithm to match all points of these two images. This matching can compare for example Euclidean distance of the points. $\endgroup$ – Tyathalae Oct 1 at 15:36
  • $\begingroup$ the way you use the term “image” is a bit ambiguous. typically these are likelihood cells or filter outputs. can you elaborate a bit like the dimensions of the cubes. it may be more accurate to say you are asking about data fusion $\endgroup$ – Stanley Pawlukiewicz Oct 1 at 16:18

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