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2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
A methodology for quality assessment in tensor images
Anchorage, AK, USA
June 23-June 28
ISBN: 978-1-4244-2339-2
Emma Munoz-Moreno, Laboratorio de Procesado de Imagen. Universidad de Valladolid, Spain
Santiago Aja-Fernandez, Laboratorio de Procesado de Imagen. Universidad de Valladolid, Spain
Marcos Martin-Fernandez, Laboratorio de Procesado de Imagen. Universidad de Valladolid, Spain
Since tensor usage has become more and more popular in image processing, the assessment of the quality between tensor images is necessary for the evaluation of the advanced processing algorithms that deal with this kind of data. In this paper, we expose the methodology that should be followed to extend well-known image quality measures to tensor data. Two of these measures based on structural comparison are adapted to tensor images and their performance is shown by a set of examples. By means of these experiments the advantages of structural based measures will be highlighted, as well as the need for considering all the tensor components in the quality assessment.
Citation:
Emma Munoz-Moreno, Santiago Aja-Fernandez, Marcos Martin-Fernandez, "A methodology for quality assessment in tensor images," cvprw, pp.1-6, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008
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