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.
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Okarma, K. (2014). Adaptation of the Combined Image Similarity Index for Video Sequences. In: S. Choras, R. (eds) Image Processing and Communications Challenges 5. Advances in Intelligent Systems and Computing, vol 233. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-01622-1_10
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DOI: https://doi.org/10.1007/978-3-319-01622-1_10
Publisher Name: Springer, Heidelberg
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