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It would be great to have all steps required for descriptor-based registration available as ops:
filter.differenceOfGaussian (exists, but with its acronym that might not be obvious for newbies: filter.dog) and filter.laplacianOfGaussian
filter.differenceOfGaussian
filter.dog
filter.laplacianOfGaussian
localExtrema(List<RefinedPeak<P>> out, RandomAccessibleInterval<T> in, T threshold?) (with optional sub-pixel localization)
localExtrema(List<RefinedPeak<P>> out, RandomAccessibleInterval<T> in, T threshold?)
descriptorMatching(InvertibleRealTransform out, List<RefinedPeak<P>> in1, List<RefinedPeak<P>> in2) or similar
descriptorMatching(InvertibleRealTransform out, List<RefinedPeak<P>> in1, List<RefinedPeak<P>> in2)
realTransform(RandomAccessibleInterval<T> in, InvertibleRealTransform transform) like implemented in Real transform #533
realTransform(RandomAccessibleInterval<T> in, InvertibleRealTransform transform)
The text was updated successfully, but these errors were encountered:
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It would be great to have all steps required for descriptor-based registration available as ops:
filter.differenceOfGaussian
(exists, but with its acronym that might not be obvious for newbies:filter.dog
) andfilter.laplacianOfGaussian
localExtrema(List<RefinedPeak<P>> out, RandomAccessibleInterval<T> in, T threshold?)
(with optional sub-pixel localization)descriptorMatching(InvertibleRealTransform out, List<RefinedPeak<P>> in1, List<RefinedPeak<P>> in2)
or similarrealTransform(RandomAccessibleInterval<T> in, InvertibleRealTransform transform)
like implemented in Real transform #533The text was updated successfully, but these errors were encountered: