Over the past few years, the availability of new and more powerful technologies and algorithms have attracted the attention of researchers and managers of academies, museums and government bodies, working in the sector of Cultural Heritage. We propose the use of a registration technique in the field of Cultural Heritage. It is based on the computation of the mutual information, which is a similarity measure coming from the information theory; it is able to determine the correct displacement (that is a geometrical transformation including subpixel translation, rotation and scaling) to align points from one image with corresponding points coming from another one of the same object or scene. Roughly speaking, mutual information is a measure of the amount of information one image contains about the other one. It is a highly performing similarity measure, when compared to previously proposed ones, such as crosscorrelation, which can often fail when dealing with multi-source images (i.e. images coming from different sensors or regarding different frequency bands), for the inherently difference of the image structures and tone dynamics.

Image Registration in the Cultural Heritage field / A.Del Mastio; A.De Rosa; A.Piva; V.Cappellini. - STAMPA. - (2006), pp. 7-31.

Image Registration in the Cultural Heritage field

DEL MASTIO, ANDREA;DE ROSA, ALESSIA;PIVA, ALESSANDRO;CAPPELLINI, VITO
2006

Abstract

Over the past few years, the availability of new and more powerful technologies and algorithms have attracted the attention of researchers and managers of academies, museums and government bodies, working in the sector of Cultural Heritage. We propose the use of a registration technique in the field of Cultural Heritage. It is based on the computation of the mutual information, which is a similarity measure coming from the information theory; it is able to determine the correct displacement (that is a geometrical transformation including subpixel translation, rotation and scaling) to align points from one image with corresponding points coming from another one of the same object or scene. Roughly speaking, mutual information is a measure of the amount of information one image contains about the other one. It is a highly performing similarity measure, when compared to previously proposed ones, such as crosscorrelation, which can often fail when dealing with multi-source images (i.e. images coming from different sensors or regarding different frequency bands), for the inherently difference of the image structures and tone dynamics.
2006
9783832513863
New Advances in Multimedia Security, Biometrics, Watermarking and Cultural Aspect
7
31
A.Del Mastio; A.De Rosa; A.Piva; V.Cappellini
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/364966
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