Can aligning a moving subject, instead of rejecting it, rescue a burst merge?

What it found

Still camera, one disc moving across a synthetic burst (Poisson shot noise, Gaussian read noise, a large sensor with 4× the pixel area). A per-pixel sub-pixel alignment to the reference frame, followed by a rejection test, reaches 37.0 dB inside the disc at 8 frames and 1 px per frame, against 31.5 dB for reject-only merging and 32.8 dB for the large frame. Over the whole image it is no better than rejecting (31.7 against 31.8 dB at 8 frames, 34.4 against 35.6 at 24) because the aligner moves 10–31% of static pixels on noise, and in the ring where the background is covered and revealed no variant gets within 4 dB of the large frame. Stylised: synthetic scenes, one flat rigid disc, translation only.

A figure from its own output

Paper, code and results

• README and method
• Experiments and results
• Code
• Tests

More in Sensing, imaging and 3D

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• How many photos does a usable 3-D reconstruction need?How many photos does a usable 3-D reconstruction need? On a synthetic object with known cameras, 12 views on a full orbit triangulate every feature, 8 views 89% and 4 or fewer at most 13%; per-point error then depends on pixel noise and pose error, not view count. Triangulation stage only (synthetic).
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Produced with AI assistance (Claude). Results are from the code in this repository and are simulated or stylised unless the abstract says otherwise; nothing here implies affiliation with or endorsement by any lab, researcher or company cited. MIT licensed.