• Journal of Broadcast Engineering
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• v.27 no.7
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• pp.985-998
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• 2022

Even after the standardization of VVC completed in 2020, continuing efforts for developing even better video coding technology are still under way. In this context, the Joint Video Experts Group (JVET) is developing various video compression technologies under the name of enhanced compression beyond VVC capability which has reported BDBR gain of -6.75%, -14.05%, and -15.25% on its test model, ECM version 5.0, respectively in Y, Cb, and Cr channels by just having a few new or improved intra coding tools. The current activity has so far adopted 11 intra coding tools beyond VVC which can generate more sophisticated predictors, reduce signaling overhead, or combine various predictors. In this tutorial paper, we will review these techniques.

• Journal of Korea Multimedia Society
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• v.22 no.7
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• pp.770-779
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• 2019

Video coding technologies are progressively becoming more efficient and complex. The Versatile Video Coding (VVC) is a new state-of-the art video compression standard that is going to be a standard, as the next generation of High Efficiency Video Coding (HEVC) standard. To explore the future video coding technologies beyond the HEVC, numerous efficient methods have been adopted by the Joint Video Exploration Team (JVET). Since then, the next generation video coding standard named as VVC and its software model called VVC Test Model (VTM) have emerged. In this paper, several important coding features for motion estimation and motion compensation in the VVC standard is introduced and analyzed in terms of the performance. Improved coding tools introduced for ME and MC in VVC, can achieve much better and good balance between coding efficiency and coding complexity compared with the HEVC.

• Journal of Broadcast Engineering
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• v.24 no.1
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• pp.41-47
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• 2019

Recently, enhanced methods on the inter merging have been being investigated in Versatile Video Coding (VVC) standardization which will be a next generation video coding standard with capability beyond the High Efficiency Video Coding (HEVC). If there is not enough motion information available in the neighboring blocks in the merge mode, zero motion candidate is inserted into the merge candidate list, which could make the coding efficiency decreased. In this paper, we propose an efficient method of constructing the merge mode candidate list to reduce the case that the zero motion is used as a candidate by generating an alternative merge candidate. Experimental results show that the proposed method gives the average BD-rate gain of 0.2% with the decoding time increase of 3% in the comparison with VTM 1.0.

• ETRI Journal
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• v.46 no.3
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• pp.538-549
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• 2024

A conventional codec aims to increase the compression efficiency for transmission and storage while maintaining video quality. However, as the number of platforms using machine vision rapidly increases, a codec that increases the compression efficiency and maintains the accuracy of machine vision tasks must be devised. Hence, the Moving Picture Experts Group created a standardization process for video coding for machines (VCM) to reduce bitrates while maintaining the accuracy of machine vision tasks. In particular, in-loop filters have been developed for improving the subjective quality and machine vision task accuracy. However, the high computational complexity of in-loop filters limits the development of a high-performance VCM architecture. We analyze the effect of an in-loop filter on the VCM performance and propose a suboptimal VCM method based on the selective activation of in-loop filters. The proposed method reduces the computation time for video coding by approximately 5% when using the enhanced compression model and 2% when employing a Versatile Video Coding test model while maintaining the machine vision accuracy and compression efficiency of the VCM architecture.

• Journal of Broadcast Engineering
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• v.23 no.4
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• pp.495-502
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• 2018

JVET (Joint Video Exploration Team) which explored evolving technologies of video coding with capabilities beyond HEVC (High Efficiency Video Coding), released a references software codec named the Joint Exploration Model (JEM) for performance verification of coding technologies. JEM has 67 intra prediction modes that extend the 35 modes of HEVC for intra prediction. Therefore, the enhancement of the coding performance is limited due to the overhead of prediction mode coding. In this paper, we analyze the probabilities of prediction modes selections, and then we propose a more efficient intra prediction mode coding based on the results of analyzed mode occurrence. In addition, we propose a context modeling for CABAC (Context-Adaptive Binary Arithmetic Coding) of the proposed mode coding. Experimental results show that the BD-rate gain is 0.02% on the AI (All Intra) coding structure compared to JEM 7.0. We need to optimize context modeling for additional coding performance enhancement.