Question

Now I’m using standard phase correlation for image stitching.
It give normal results, but on hard images it gives wrong result, but Stitch 2D plugin in ImageJ(FIJI) gives good result in the majority of cases.
The algorithm used in plugin described in this paper http://bioinformatics.oxfordjournals.org/content/25/11/1463.full.pdf
But i can’t understand it.
“In real images, however,F−1(Q) contains several peaks marking different
translations with high correlation. Moreover, each peak describes eight
different possible translations (in 3D) due to the periodicity of the Fourier
space. To determine the correct shift, we select the n highest local maxima
(3×3×3 neighborhood) from F−1(Q) and evaluate their eight possible
translations by means of cross-correlation on the overlapping area of the
images A,B. The peak with the highest correlation is selected as translation
between the two images. If none of the peaks is above a certain limit the
tiles are assumed to be non-overlapping.”
can anyone explain how to implement it?

Answer 1

From the quote it looks as if:

1. They use phase correllation to find multiple candidates (“we select the n highest local maxima (3×3×3 neighborhood) from F−1(Q)”) for the overlapping segment between two images
2. And then they use some matching in the original image data (“by means of cross-correlation on the overlapping area of the images A,B.”)
3. To select the best candidate from those(“The peak with the highest correlation is selected as translation between the two images.”),
4. If that best candidate matches good enough (“If none of the peaks is above a certain limit the tiles are assumed to be non-overlapping.”).