Video Quality Assessment Using Spatio-Velocity Contrast Sensitivity Function

Keita HIRAI  Jambal TUMURTOGOO  Ayano KIKUCHI  Norimichi TSUMURA  Toshiya NAKAGUCHI  Yoichi MIYAKE  

IEICE TRANSACTIONS on Information and Systems   Vol.E93-D   No.5   pp.1253-1262
Publication Date: 2010/05/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E93.D.1253
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Image Processing and Video Processing
objective video quality assessment,  spatio-velocity contrast sensitivity function,  image diffrence,  subjective evaluation,  rank order correlation coefficient,  

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Due to the development and popularization of high-definition televisions, digital video cameras, Blu-ray discs, digital broadcasting, IP television and so on, it plays an important role to identify and quantify video quality degradations. In this paper, we propose SV-CIELAB which is an objective video quality assessment (VQA) method using a spatio-velocity contrast sensitivity function (SV-CSF). In SV-CIELAB, motion information in videos is effectively utilized for filtering unnecessary information in the spatial frequency domain. As the filter to apply videos, we used the SV-CSF. It is a modulation transfer function of the human visual system, and consists of the relationship among contrast sensitivities, spatial frequencies and velocities of perceived stimuli. In the filtering process, the SV-CSF cannot be directly applied in the spatial frequency domain because spatial coordinate information is required when using velocity information. For filtering by the SV-CSF, we obtain video frames separated in spatial frequency domain. By using velocity information, the separated frames with limited spatial frequencies are weighted by contrast sensitivities in the SV-CSF model. In SV-CIELAB, the criteria are obtained by calculating image differences between filtered original and distorted videos. For the validation of SV-CIELAB, subjective evaluation experiments were conducted. The subjective experimental results were compared with SV-CIELAB and the conventional VQA methods such as CIELAB color difference, Spatial-CIELAB, signal to noise ratio and so on. From the experimental results, it was shown that SV-CIELAB is a more efficient VQA method than the conventional methods.