A computationally scalable fast intra coding scheme for HEVC video encoder
The High Efficiency Video Coding (HEVC) adopts 35 intra prediction modes to provide a more precise intra prediction. As a result, HEVC intra coding is much more complex. To provide a flexible solution for battery-powered devices, which include varying power budgets based on battery level, this paper...
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| Vydáno v: | Multimedia tools and applications Ročník 78; číslo 9; s. 11607 - 11630 |
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| Jazyk: | angličtina |
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01.05.2019
Springer Nature B.V |
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| ISSN: | 1380-7501, 1573-7721 |
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| Abstract | The High Efficiency Video Coding (HEVC) adopts 35 intra prediction modes to provide a more precise intra prediction. As a result, HEVC intra coding is much more complex. To provide a flexible solution for battery-powered devices, which include varying power budgets based on battery level, this paper jointly employs statistical distribution of different intra modes, and texture analysis. While the statistical information specifies the most efficient modes for extremely low power budgets, for moderate to high power budgets the best angular modes are predicted by analyzing the residual of the Planar mode, which is demonstrated to represent the dominant edges of the block. Moreover, a scheme is presented that further reduces the complexity by predicting the more important DC and Planar modes using the information provided by the entropy coder. The proposed method imposes almost no computational overhead since it utilizes the existing internal operators of HEVC. Ultimately, an intra prediction scheme with seven predefined levels of complexity is presented that provides coding for various power budgets and devices with various capabilities. The highest level of this scheme provides ~23% total encoding time reduction compared to HM, in all-intra configuration, with only 0.78% penalty on BD-Rate for high end devices. While the lowest level makes encoding possible for extremely low power devices and low battery plans with ~52% time reduction (almost the entire share of intra coding) at the cost of 9.6% BD-Rate, which is shown to be nearly minimal for this level of processing power. |
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| AbstractList | The High Efficiency Video Coding (HEVC) adopts 35 intra prediction modes to provide a more precise intra prediction. As a result, HEVC intra coding is much more complex. To provide a flexible solution for battery-powered devices, which include varying power budgets based on battery level, this paper jointly employs statistical distribution of different intra modes, and texture analysis. While the statistical information specifies the most efficient modes for extremely low power budgets, for moderate to high power budgets the best angular modes are predicted by analyzing the residual of the Planar mode, which is demonstrated to represent the dominant edges of the block. Moreover, a scheme is presented that further reduces the complexity by predicting the more important DC and Planar modes using the information provided by the entropy coder. The proposed method imposes almost no computational overhead since it utilizes the existing internal operators of HEVC. Ultimately, an intra prediction scheme with seven predefined levels of complexity is presented that provides coding for various power budgets and devices with various capabilities. The highest level of this scheme provides ~23% total encoding time reduction compared to HM, in all-intra configuration, with only 0.78% penalty on BD-Rate for high end devices. While the lowest level makes encoding possible for extremely low power devices and low battery plans with ~52% time reduction (almost the entire share of intra coding) at the cost of 9.6% BD-Rate, which is shown to be nearly minimal for this level of processing power. |
| Author | Hashemi, Mahmoud Reza Ghanbari, Mohammad Pakdaman, Farhad Hosseini, Elahe |
| Author_xml | – sequence: 1 givenname: Elahe surname: Hosseini fullname: Hosseini, Elahe organization: School of Electrical and Computer Engineering, University of Tehran – sequence: 2 givenname: Farhad orcidid: 0000-0001-6526-3811 surname: Pakdaman fullname: Pakdaman, Farhad organization: School of Electrical and Computer Engineering, University of Tehran – sequence: 3 givenname: Mahmoud Reza surname: Hashemi fullname: Hashemi, Mahmoud Reza email: rhashemi@ut.ac.ir organization: School of Electrical and Computer Engineering, University of Tehran – sequence: 4 givenname: Mohammad surname: Ghanbari fullname: Ghanbari, Mohammad organization: School of Electrical and Computer Engineering, University of Tehran, School of Computer Science and Electronic Engineering, University of Essex |
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| CitedBy_id | crossref_primary_10_1007_s11042_019_07989_0 crossref_primary_10_1007_s11042_019_08593_y crossref_primary_10_1109_ACCESS_2024_3521578 crossref_primary_10_1007_s11042_019_08426_y crossref_primary_10_1007_s11042_021_11678_2 crossref_primary_10_1007_s11554_019_00864_z crossref_primary_10_1007_s11554_022_01223_1 crossref_primary_10_1016_j_image_2021_116177 crossref_primary_10_3390_electronics10090985 crossref_primary_10_32604_cmc_2022_019541 crossref_primary_10_1007_s00034_020_01482_y crossref_primary_10_1007_s11042_022_12582_z crossref_primary_10_1007_s11042_020_08915_5 crossref_primary_10_3390_electronics10151839 crossref_primary_10_1007_s11554_020_00996_7 crossref_primary_10_1016_j_jvcir_2022_103594 |
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| Keywords | Video compression HEVC Power-aware video coding Intra prediction |
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