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Adaptation of the Combined Image Similarity Index for Video Sequences

  • Krzysztof Okarma
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 233)

Summary

One of the most relevant areas of research in the image analysis domain is the development of automatic image quality assessment methods which should be consistent with human perception of various distortions. During last years several metrics have been proposed as well as their combinations which lead to highly linear correlation with subjective opinions. One of the recently proposed ideas is the Combined Image Similarity Index which is the nonlinear combination of three metrics outperforming most of currently known ones for major image datasets. In this paper the applicability and extension of this metric for video quality assessment purposes is analysed and the obtained performance results are compared with some other metrics using the video quality assessment database recently developed at École Polytechnique Fédérale de Lausanne and Politecnico di Milano for quality monitoring over IP networks, known as EPFL-PoliMI dataset.

Keywords

Video Sequence Video Quality Mean Opinion Score Image Quality Assessment Subjective Score 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Faculty of Electrical Engineering, Department of Signal Processing and Multimedia EngineeringWest Pomeranian University of Technology, SzczecinSzczecinPoland

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