Reduced-reference Video Quality Metric Using Spatio-temporal Activity Information

Abstract

Monitoring and maintaining acceptab le Quality of Experience is of great importance to video service providers. Perceived visual quality of transmitted video via wireless networks can b e degraded b y transmission errors. This paper presents a reduced-reference video quality metric of very low complexity and overhead that makes use of frame b ased spatial (SI) and temporal (TI) activity levels to monitor the effect of channel errors on video transmitted over error prone networks. The performance of the metric is evaluated relative to that of a numb er of full and reduced reference metrics. The proposed metric outperforms some of the most popular full reference metrics whilst requiring very little overhead.

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“…However, [22] the maximum accuracy rate is registered as 97.24 percent, which is shown by IICBMergeFS in combination with CNN classifier [23]. The second better suitable classifier to the proposed IICBMergeFS technique is [24], [25]. SVM and the recorded accuracy rate is 88.24 percent.…”