An add-on video compression codec based on content-adaptive sparse super-resolution reconstructions

Shu Yang; Jianmin Jiang

doi:10.1117/12.2266112

8 February 2017 An add-on video compression codec based on content-adaptive sparse super-resolution reconstructions

Shu Yang, Jianmin Jiang

Proceedings Volume 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016); 102251I (2017) https://doi.org/10.1117/12.2266112
Event: Eighth International Conference on Graphic and Image Processing, 2016, Tokyo, Japan

Abstract

In this paper, we introduce an idea of content-adaptive sparse reconstruction to achieve optimized magnification quality for those down sampled video frames, to which two stages of pruning are applied to select the closest correlated images for construction of an over-complete dictionary and drive the sparse representation of its enlarged frame. In this way, not only the sampling and dictionary training process is accelerated and optimized in accordance with the input frame content, but also an add-on video compression codec can be further developed by applying such scheme as a preprocessor to any standard video compression algorithm. Our extensive experiments illustrate that (i) the proposed content-adaptive sparse reconstruction outperforms the existing benchmark in terms of super-resolution quality; (ii) When applied to H.264, one of the international video compression standards, the proposed add-on video codec can achieve three times more compression while maintaining competitive decoding quality.

Citation Download Citation

Shu Yang and Jianmin Jiang "An add-on video compression codec based on content-adaptive sparse super-resolution reconstructions", Proc. SPIE 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016), 102251I (8 February 2017); https://doi.org/10.1117/12.2266112

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KEYWORDS

Video compression

Video

Super resolution

Reconstruction algorithms

Image resolution

Associative arrays

Image compression

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