image processing - How to align two different pictures in such a way, that they match as close as possible? -

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i need automatically align image b on top of image a in such way, contents of image match possible.

the images can shifted in x/y directions , rotated 5 degrees on z, won't distorted (i.e. scaled or keystoned).

maybe can recommend links or books on topic, or share thoughts how such alignment of images done.

if there wasn't rotation problem, try compare rows of pixels brute-force method until find match, , know offset , can align image.

do need ai this?

i'm having hard time finding resources on image processing go detail how these alignment-algorithms work.

so people in case first find points in images match compute best transformation matrix least squares. point matching not particularly simple , times use human input task, have time calibrating cameras. anyway, if want automate process can use feature extraction techniques find matching points, there volumes of research papers written on topic , standard computer vision text have chapter on this. once have n matching points, solving least squares transformation matrix pretty straightforward and, again, can found in computer vision text, i'll assume got covered.

if don't want find point correspondences directly optimize rotation , translation using steepest descent, trouble non-convex there no guarantees find correct transformation. random restarts or simulated annealing or other global optimization tricks on top of this, work. can't find references problem, it's digital image stabilization algorithm had implement when took computer vision many years ago, here relevant slides though, @ "stabilization revisited". yes, know slides terrible, didn't make them :) however, method determining gradient quite elegant one, since finite difference intractable.

edit: found paper went on how here, it's great paper , explains lucas-kanade algorithm nicely. also, this site has whole lot of material , source code on image alignment useful.


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