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Jointly probability-based fast intra prediction algorithm for spatial SHVC.

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Title: Jointly probability-based fast intra prediction algorithm for spatial SHVC.
Authors: Li, Weian1 (AUTHOR), Ou, Weihua1 (AUTHOR), Wang, Hongbing1 (AUTHOR) hbwang@gznu.edu.cn, Wu, Yang1 (AUTHOR), Zhong, Yunhao1 (AUTHOR)
Source: EURASIP Journal on Image & Video Processing. 11/4/2025, Vol. 2025 Issue 1, p1-20. 20p.
Subjects: Video coding, Video compression, Texture analysis (Image processing), Rate distortion theory
Abstract: Since Spatial Scalable High Efficiency Video Coding (SSHVC) utilizes multi-layer encoding and inter-layer prediction, it has extremely high coding complexity which has severely hindered its wide spread. In order to improve coding speed, we develop a fast intra coding algorithm to improve coding speed of SSHVC. First, we utilize the textural feature to obtain the probabilities of using Coding Units (CUs), so as to predict candidate CUs and exclude unlikely ones. Second, we jointly utilize the textural features, the neighboring Coding Modes (CMs) and Rate Distortion (RD) cost to obtain the probability of Intra Mode (IM), which is then combined with the probability of its collocated CU to exclude unlikely IMs. Finally, we investigate distribution of Direction Modes (DMs), which are then combined with the probability of their collocated CU to predict candidate DMs and exclude unlikely ones. Experimental results demonstrate that the proposed algorithm can significantly improve coding speed by 78.64% with negligible coding efficiency change by a 0.27% decrease in BDBR. [ABSTRACT FROM AUTHOR]
Copyright of EURASIP Journal on Image & Video Processing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Jointly probability-based fast intra prediction algorithm for spatial SHVC.
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  Data: <searchLink fieldCode="AR" term="%22Li%2C+Weian%22">Li, Weian</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ou%2C+Weihua%22">Ou, Weihua</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Hongbing%22">Wang, Hongbing</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> hbwang@gznu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Wu%2C+Yang%22">Wu, Yang</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhong%2C+Yunhao%22">Zhong, Yunhao</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22EURASIP+Journal+on+Image+%26+Video+Processing%22">EURASIP Journal on Image & Video Processing</searchLink>. 11/4/2025, Vol. 2025 Issue 1, p1-20. 20p.
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  Data: <searchLink fieldCode="DE" term="%22Video+coding%22">Video coding</searchLink><br /><searchLink fieldCode="DE" term="%22Video+compression%22">Video compression</searchLink><br /><searchLink fieldCode="DE" term="%22Texture+analysis+%28Image+processing%29%22">Texture analysis (Image processing)</searchLink><br /><searchLink fieldCode="DE" term="%22Rate+distortion+theory%22">Rate distortion theory</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: Since Spatial Scalable High Efficiency Video Coding (SSHVC) utilizes multi-layer encoding and inter-layer prediction, it has extremely high coding complexity which has severely hindered its wide spread. In order to improve coding speed, we develop a fast intra coding algorithm to improve coding speed of SSHVC. First, we utilize the textural feature to obtain the probabilities of using Coding Units (CUs), so as to predict candidate CUs and exclude unlikely ones. Second, we jointly utilize the textural features, the neighboring Coding Modes (CMs) and Rate Distortion (RD) cost to obtain the probability of Intra Mode (IM), which is then combined with the probability of its collocated CU to exclude unlikely IMs. Finally, we investigate distribution of Direction Modes (DMs), which are then combined with the probability of their collocated CU to predict candidate DMs and exclude unlikely ones. Experimental results demonstrate that the proposed algorithm can significantly improve coding speed by 78.64% with negligible coding efficiency change by a 0.27% decrease in BDBR. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of EURASIP Journal on Image & Video Processing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1186/s13640-025-00683-2
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      – Code: eng
        Text: English
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      – SubjectFull: Texture analysis (Image processing)
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      – SubjectFull: Rate distortion theory
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              Text: 11/4/2025
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