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Simultaneous Registration of Image Sequences – a novel singular value based images similarity measure
Author(s) -
Brehmer Kai,
Wacker Benjamin,
Modersitzki Jan
Publication year - 2018
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/pamm.201800370
Subject(s) - image (mathematics) , artificial intelligence , image registration , similarity (geometry) , computation , rank (graph theory) , computer science , computer vision , image processing , sequence (biology) , similarity measure , pattern recognition (psychology) , measure (data warehouse) , mathematics , image restoration , algorithm , data mining , combinatorics , biology , genetics
The comparison of images is an important task in image processing. For a comparison of two images, a variety of measures has been suggested. However, applications such as dynamic imaging or serial sectioning provide a series of many images to be compared. When these images are to be registered, the standard approach is to sequentially align the j ‐th image with respect to its neighbours and sweep with respect to j . One of the disadvantages is that information is distributed only locally. We introduce an alternative so‐called SqN approach. SqN is based on the Schatten‐ q ‐norm of the image sequence gradients, i.e. rank information of image gradients of the whole image sequence. With this approach, information is transported globally. Our experiments show that SqN gives at least comparable registration results to standard distance measures but its computation is about six times faster.