Arithmetic coding using hierarchical dependency context model for H.264/AVC video coding

2015 ◽  
Vol 75 (12) ◽  
pp. 7351-7370 ◽  
Author(s):  
Min Gao ◽  
Qiang Wang ◽  
Debin Zhao ◽  
Wen Gao
Entropy ◽  
2021 ◽  
Vol 23 (8) ◽  
pp. 983
Author(s):  
Jingjian Li ◽  
Wei Wang ◽  
Hong Mo ◽  
Mengting Zhao ◽  
Jianhua Chen

A distributed arithmetic coding algorithm based on source symbol purging and using the context model is proposed to solve the asymmetric Slepian–Wolf problem. The proposed scheme is to make better use of both the correlation between adjacent symbols in the source sequence and the correlation between the corresponding symbols of the source and the side information sequences to improve the coding performance of the source. Since the encoder purges a part of symbols from the source sequence, a shorter codeword length can be obtained. Those purged symbols are still used as the context of the subsequent symbols to be encoded. An improved calculation method for the posterior probability is also proposed based on the purging feature, such that the decoder can utilize the correlation within the source sequence to improve the decoding performance. In addition, this scheme achieves better error performance at the decoder by adding a forbidden symbol in the encoding process. The simulation results show that the encoding complexity and the minimum code rate required for lossless decoding are lower than that of the traditional distributed arithmetic coding. When the internal correlation strength of the source is strong, compared with other DSC schemes, the proposed scheme exhibits a better decoding performance under the same code rate.


Author(s):  
Dinh - Lam Tran ◽  
Viet - Huong Pham ◽  
Hung K Nguyen ◽  
Xuan - Tu Tran

High-Efficiency Video Coding (HEVC), also known as H.265 and MPEG-H Part 2, is the newest video coding standard developed to address the increasing demand for higher resolutions and frame rates. In comparison to its predecessor H.264/AVC, HEVC achieved almost double of compression performance that is capable to process high quality video sequences (UHD 4K, 8K; high frame rates) in a wide range of applications. Context-Adaptive Baniray Arithmetic Coding (CABAC) is the only entropy coding method in HEVC, whose principal algorithm is inherited from its predecessor. However, several aspects of the method that exploits it in HEVC are different, thus HEVC CABAC supports better coding efficiency. Effectively, pipeline and parallelism in CABAC hardware architectures are prospective methods in the implementation of high performance CABAC designs. However, high data dependence and serial nature of bin-to-bin processing in CABAC algorithm pose many challenges for hardware designers. This paper provides an overview of CABAC hardware implementations for HEVC targeting high quality, low power video applications, addresses challenges of exploiting it in different application scenarios and then recommends several predictive research trends in the future.


Author(s):  
Alexey Filippov ◽  
Vasily Rufitskiy ◽  
Alexander Karabutov ◽  
Jianle Chen

In this paper, we present a technique that is known as Residual Sign Prediction in Transform Domain (TDRSP) and is aimed at increasing compression performance by reducing the bits overhead of residue sign. These signs are typically coded by entropy coders in bypass mode that results in the high cost of sign bins which require 1 bit per bin in a bitstream. TDRSP allows us to reduce this cost by predicting residue signs so that the probability of a guess is significantly higher than 50%. Hence, arithmetic coding with contexts becomes applicable to the signs. In contrast to Residual Sign Prediction (RSP) performed in spatial domain, TDRSP avoids switching between domains and carries out calculations completely in transform domain to efficiently decrease the computational complexity of RSP. Simulations performed on top of Versatile Video Coding test model reference software (VTM-1.0) in accordance with the Joint Video Experts Team common test conditions show that more than 2.0% and up to 1.8% of the Bjøntegaard Delta rate can be achieved for All Intra and Random Access configurations, respectively.


2019 ◽  
Vol 76 ◽  
pp. 118-124 ◽  
Author(s):  
Junwei Zhou ◽  
Yincheng Fu ◽  
Yanchao Yang ◽  
Anthony T.S. Ho

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