Reduced Complexity Superresolution for Low-Bitrate Video Compression

Evolving video applications impose requirements for high image quality, low bitrate, and/or small computational cost. This paper combines state-of-the-art coding and superresolution (SR) techniques to improve video compression both in terms of coding efficiency and complexity. The proposed approach...

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Veröffentlicht in:IEEE transactions on circuits and systems for video technology Jg. 26; H. 2; S. 332 - 345
Hauptverfasser: Georgis, Georgios, Lentaris, George, Reisis, Dionysios
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.02.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Bit rate
Codec
Codecs
Coding
Complexity
Complexity theory
Computational efficiency
Computing time
Decoding
Encoding
high definition video
Image coding
Image compression
Image quality
Interpolation
low-complexity codecs
Noise levels
Parameterization
Parametrization
PSNR
Quality
Reduction
Rescaling
Signal quality
singleimage
State of the art
Super-resolution
Video compression
High-definition video
single image
superresolution (SR)
video compression
low-complexity codecs
ISSN:1051-8215, 1558-2205
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Zusammenfassung:Evolving video applications impose requirements for high image quality, low bitrate, and/or small computational cost. This paper combines state-of-the-art coding and superresolution (SR) techniques to improve video compression both in terms of coding efficiency and complexity. The proposed approach improves a generic decimation-quantization compression scheme by introducing low complexity single-image SR techniques for rescaling the data at the decoder side and by jointly exploring/optimizing the downsampling/upsampling processes. The enhanced scheme achieves improvement of the quality and system's complexity compared with conventional codecs and can be easily modified to meet various diverse requirements, such as effectively supporting any off-the-shelf video codec, for instance H.264/Advanced Video Coding or High Efficiency Video Coding. Our approach builds on studying the generic scheme's parameterization with common rescaling techniques to achieve 2.4-dB peak signal-to-noise ratio (PSNR) quality improvement at low-bitrates compared with the conventional codecs and proposes a novel SR algorithm to advance the critical bitrate at the level of 10 Mb/s. The evaluation of the SR algorithm includes the comparison of its performance to other image rescaling solutions of the literature. The results show quality improvement by 5-dB PSNR over straightforward interpolation techniques and computational time reduction by three orders of magnitude when compared with the highly involved methods of the field. Therefore, our algorithm proves to be most suitable for use in reduced complexity downsampled compression schemes.
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ISSN:1051-8215
1558-2205
DOI:10.1109/TCSVT.2015.2389431