Abstract | ||
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Hybrid digital-analog (HDA) transmission has gained increasing attention recently in the context of wireless video delivery, for its ability to simultaneously achieve high transmission efficiency and smooth quality adaptation. However, previous systems are optimized solely based on the mean squared error criterion without taking the perceptual video quality into consideration. In this work, we propose a structure-preserving HDA video delivery system, named SharpCast, to improve both the objective and subjective visual quality. SharpCast decomposes a video into content part and structure part. The latter is important to the human perception and therefore is protected with a robust digital transmission scheme. Then, the energy-intensive part in the content information is extracted and transmitted in digital for energy efficiency while the residual is transmitted in analog to achieve the desired smooth adaptation. We formulate the resource (power and bandwidth) allocation problem in SharpCast and solve the problem with a greedy strategy. Evaluations over nine standard 720p video sequences show that the proposed SharpCast system outperforms the state-of-the-art digital, analog and HDA schemes by a notable margin in both peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). |
Year | DOI | Venue |
---|---|---|
2015 | 10.1109/TMM.2015.2451956 | Multimedia, IEEE Transactions |
Keywords | Field | DocType |
Bandwidth,Wireless communication,Channel coding,Discrete cosine transforms,Visualization,PSNR | Wireless network,Wireless,Data transmission,Computer science,Computer network,Mean squared error,Real-time computing,Artificial intelligence,Residual,Computer vision,Efficient energy use,Visualization,Bandwidth (signal processing) | Journal |
Volume | Issue | ISSN |
PP | 99 | 1520-9210 |
Citations | PageRank | References |
11 | 0.65 | 15 |
Authors | ||
4 |
Name | Order | Citations | PageRank |
---|---|---|---|
He, D. | 1 | 33 | 13.67 |
chong luo | 2 | 696 | 47.36 |
Cuiling Lan | 3 | 283 | 24.49 |
Feng Wu | 4 | 3635 | 295.09 |