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20240229162818.0 |
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231225s2020 xx |||||o 00| ||eng c |
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|a 10.1109/TIP.2020.2988437
|2 doi
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|a pubmed24n1308.xml
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|a DE-627
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|e rakwb
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|a eng
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| 100 |
1 |
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|a Duanmu, Zhengfang
|e verfasserin
|4 aut
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| 245 |
1 |
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|a Characterizing Generalized Rate-Distortion Performance of Video Coding
|b An Eigen Analysis Approach
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|c 2020
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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|a ƒa Online-Ressource
|b cr
|2 rdacarrier
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|a Date Revised 27.02.2024
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|a published: Print-Electronic
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|a Citation Status Publisher
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|a Rate-distortion (RD) theory is at the heart of lossy data compression. Here we aim to model the generalized RD (GRD) trade-off between the visual quality of a compressed video and its encoding profiles (e.g., bitrate and spatial resolution). We first define the theoretical functional space W of the GRD function by analyzing its mathematical properties. We show that W is a convex set in a Hilbert space, inspiring a computational model of the GRD function, and a method of estimating model parameters from sparse measurements. To demonstrate the feasibility of our idea, we collect a large-scale database of real-world GRD functions, which turn out to live in a low-dimensional subspace of W. Combining the GRD reconstruction framework and the learned low-dimensional space, we create a low-parameter eigen GRD method to accurately estimate the GRD function of a source video content from only a few queries. Experimental results on the database show that the learned GRD method significantly outperforms state-of-the-art empirical RD estimation methods both in accuracy and efficiency. Last, we demonstrate the promise of the proposed model in video codec comparison
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|a Journal Article
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|a Liu, Wentao
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Li, Zhuoran
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Ma, Kede
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Wang, Zhou
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g (2020) vom: 27. Apr.
|w (DE-627)NLM09821456X
|x 1941-0042
|7 nnns
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| 773 |
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|g year:2020
|g day:27
|g month:04
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|u http://dx.doi.org/10.1109/TIP.2020.2988437
|3 Volltext
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|a AR
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|j 2020
|b 27
|c 04
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