2010Elektronika ir ElektrotechnikaOpen access

Estimation of Degraded Video Quality of Mobile H.264/AVC Video Streaming

Šarūnas Paulikas

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Abstract

The problem of estimation of subjective video quality of distorted video sequences for mobile video streaming is addressed. Widely spreading mobile communication systems and increasing data transmission rates expand variety of multimedia services. One of such services is video straming. So it is important to asses quality of this service. Consumers of video streaming are humans, and quality assessment must account human perception characteristics. Most of the well-known video quality estimation methods, such as Peak Signal to Noise Ratio (PSNR), Structural Similarity (SSIM), Video Quality Metric (VQM), etc. are based on the presence of full or reduced reference video sequence. However, in order to estimate user experienced video quality, methods with no reference must be employed. Such existing methods as quality metrics usually use bit-error rate that has low correlation with by human perceived video quality. More advanced methods usually require too much processing power that cannot be obtained in handled mobile devices. It is shown that video quality estimation method with no reference and low computation complexity could be developed basing on H.264/AVC video stream structure. Such method is suitable for implementation in mobile devices with low processing power. Ill. 4, bibl. 11 (in English; summaries in English, Russian and Lithuanian).

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What this paper is about

The problem of estimation of subjective video quality of distorted video sequences for mobile video streaming is addressed. Widely spreading mobile communication systems and increasing data transmission rates expand variety of multimedia services. One of such services is video straming. So it is important to asses quality of this service. Consumers of video streaming are humans, and quality assessment must account human perception characteristics. Most of the well-known video quality estimation methods, such as Peak Signal to Noise Ratio (PSNR), Structural Similarity (SSIM), Video Quality Metric (VQM), etc. are based on the presence of full or reduced reference video sequence. However, in order to estimate user experienced video quality, methods with no reference must be employed. Such existing methods as quality metrics usually use bit-error rate that has low correlation with by human perceived video quality. More advanced methods usually require too much processing power that cannot be obtained in handled mobile devices. It is shown that video quality estimation method with no reference and low computation complexity could be developed basing on H.264/AVC video stream structure. Such method is suitable for implementation in mobile devices with low processing power. Ill. 4, bibl. 11 (in English; summaries in English, Russian and Lithuanian).

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Available abstract

The problem of estimation of subjective video quality of distorted video sequences for mobile video streaming is addressed. Widely spreading mobile communication systems and increasing data transmission rates expand variety of multimedia services. One of such services is video straming. So it is important to asses quality of this service. Consumers of video streaming are humans, and quality assessment must account human perception characteristics. Most of the well-known video quality estimation methods, such as Peak Signal to Noise Ratio (PSNR), Structural Similarity (SSIM), Video Quality Metric (VQM), etc. are based on the presence of full or reduced reference video sequence. However, in order to estimate user experienced video quality, methods with no reference must be employed. Such existing methods as quality metrics usually use bit-error rate that has low correlation with by human perceived video quality. More advanced methods usually require too much processing power that cannot be obtained in handled mobile devices. It is shown that video quality estimation method with no reference and low computation complexity could be developed basing on H.264/AVC video stream structure. Such method is suitable for implementation in mobile devices with low processing power. Ill. 4, bibl. 11 (in English; summaries in English, Russian and Lithuanian).

Key concepts: Video quality, Computer science, Rate–distortion optimization, Video compression picture types, Subjective video quality, PEVQ, Video processing, Video tracking

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