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Proceedings Paper

A human visual system model for no-reference digital video quality estimation
Author(s): Francesco Massidda; Cristian Perra; Daniele D. Giusto
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Paper Abstract

No-reference metrics are very useful for In-Service streaming applications. In this paper a blind measure for video quality assessment is presented. The proposed approach takes into account HVS Luminance Masking, Contrast Sensitivity and Temporal Masking. Video distortion level is then computed evaluating blockiness, blurring and moving artifacts. A global quality index is obtained using a multi-dimensional pooling algorithm (block, temporal window, frame, and sequence levels). Different video standard and several compression ratios have been used. A non-linear regression method has been derived, in order to obtain high linear and rank order correlation factors between human observer ratings and the proposed HVS-based index. Validation tests have been developed to assess index performance and computational complexity. Experimental results show that high correlation factors are obtained using the HVS models.

Paper Details

Date Published: 17 January 2005
PDF: 12 pages
Proc. SPIE 5668, Image Quality and System Performance II, (17 January 2005); doi: 10.1117/12.594039
Show Author Affiliations
Francesco Massidda, Univ. degli Studi di Cagliari (Italy)
Cristian Perra, Univ. degli Studi di Cagliari (Italy)
Daniele D. Giusto, Univ. degli Studi di Cagliari (Italy)

Published in SPIE Proceedings Vol. 5668:
Image Quality and System Performance II
Rene Rasmussen; Yoichi Miyake, Editor(s)

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