Spatiotemporal super-resolution for low bitrate H.264 video

N Anantrasirichai; CN Canagarajah

doi:10.1109/ICIP.2010.5651088

Spatiotemporal super-resolution for low bitrate H.264 video

N Anantrasirichai, CN Canagarajah

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

5 Citations (Scopus)

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Abstract

Super-resolution and frame interpolation enhance low resolution low-framerate videos. Such techniques are especially important for limited bandwidth communications. This paper proposes a novel technique to up-scale videos compressed with H.264 at low bit-rate both in spatial and temporal dimensions. A quantisation noise model is used in the super-resolution estimator, designed for low bitrate video, and a weighting map for decreasing inaccuracy of motion estimation are proposed. Results show improvement both in rate-distortion and perceived image quality.

Translated title of the contribution	Spatiotemporal super-resolution for low bitrate H.264 video
Original language	English
Title of host publication	IEEE International Conference on Image Processing
Pages	2809 - 2812
Number of pages	4
DOIs	https://doi.org/10.1109/ICIP.2010.5651088
Publication status	Published - 26 Sept 2010

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Conference Organiser: IEEE

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10.1109/ICIP.2010.5651088

Anantrasirichai
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abstract = "Super-resolution and frame interpolation enhance low resolution low-framerate videos. Such techniques are especially important for limited bandwidth communications. This paper proposes a novel technique to up-scale videos compressed with H.264 at low bit-rate both in spatial and temporal dimensions. A quantisation noise model is used in the super-resolution estimator, designed for low bitrate video, and a weighting map for decreasing inaccuracy of motion estimation are proposed. Results show improvement both in rate-distortion and perceived image quality.",

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N2 - Super-resolution and frame interpolation enhance low resolution low-framerate videos. Such techniques are especially important for limited bandwidth communications. This paper proposes a novel technique to up-scale videos compressed with H.264 at low bit-rate both in spatial and temporal dimensions. A quantisation noise model is used in the super-resolution estimator, designed for low bitrate video, and a weighting map for decreasing inaccuracy of motion estimation are proposed. Results show improvement both in rate-distortion and perceived image quality.

AB - Super-resolution and frame interpolation enhance low resolution low-framerate videos. Such techniques are especially important for limited bandwidth communications. This paper proposes a novel technique to up-scale videos compressed with H.264 at low bit-rate both in spatial and temporal dimensions. A quantisation noise model is used in the super-resolution estimator, designed for low bitrate video, and a weighting map for decreasing inaccuracy of motion estimation are proposed. Results show improvement both in rate-distortion and perceived image quality.

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M3 - Conference Contribution (Conference Proceeding)

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BT - IEEE International Conference on Image Processing

ER -

Spatiotemporal super-resolution for low bitrate H.264 video

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