8 March 2011 Image fusion for art analysis
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Abstract
Our paper addresses problem of multi-modal data acquisition and the following data visualization for art analysis and interpretation. Various types of modalities for acquisition of digital images are used for art analysis. The data we can obtain using various modalities differ in two ways. The acquired images can differ by their mutual geometry and possibly by their radiometric quality. These are the differences we would like to remove. The group of differences we are interested in are details or characteristics of an artwork, which are apparent just in the certain modality and which bring us new information. The two listed groups represent two categories of image processing methods we have to deal with. The first one is represented by image preprocessing methods such as data enhancement and restoration algorithms, the second class includes effective ways how to combine the acquired information into one image - image fusion. In our paper we present image quality enhancement for microscopic multi-modal data and their segmentation and recent results in data fusion and visualization for art analysis are demonstrated from the second category of methods.
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Barbara Zitová, Barbara Zitová, Miroslav Beneš, Miroslav Beneš, Jan Blažek, Jan Blažek, } "Image fusion for art analysis", Proc. SPIE 7869, Computer Vision and Image Analysis of Art II, 786908 (8 March 2011); doi: 10.1117/12.872420; https://doi.org/10.1117/12.872420
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