One-pass encoding algorithm for adaptive loop filter in high-efficiency video coding

2011 ◽  
Author(s):  
Chia-Yang Tsai ◽  
Ching-Yeh Chen ◽  
Chih-Ming Fu ◽  
Yu-Wen Huang ◽  
Shawmin Lei
Keyword(s):  
Video Coding ◽  
High Efficiency ◽  
High Efficiency Video Coding ◽  
Loop Filter ◽  
Adaptive Loop Filter

scholarly journals Performance Comparison of Weak Filtering in HEVC and VVC

Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 960
Author(s):  
Junghyun Lee ◽  
Jechang Jeong
Keyword(s):  
Video Coding ◽  
High Efficiency ◽  
Performance Comparison ◽  
Video Codec ◽  
Experimental Result ◽  
Test Model ◽  
High Efficiency Video Coding ◽  
Loop Filter ◽  
Filtering Method ◽  
Filter Process

This study describes the need to improve the weak filtering method for the in-loop filter process used identically in versatile video coding (VVC) and high efficiency video coding (HEVC). The weak filtering process used by VVC has been adopted and maintained since Draft Four during H.265/advanced video coding (AVC) standardization. Because the encoding process in the video codec utilizes block structural units, deblocking filters are essential. However, as many of the deblocking filters require a complex calculation process, it is necessary to ensure that they have a reasonable effect. This study evaluated the performance of the weak filtering portion of the VVC and confirmed that it is not functioning effectively, unlike its performance in the HEVC. The method of excluding the whole of weak filtering from VVC, which is a non-weak filtering method, should be considered in VVC standardization. In experimental result in this study, the non-weak filtering method brings 0.40 Y-Bjontegaard-Delta Bit-Rate (BDBR) gain over VVC Test Model (VTM) 6.0.

scholarly journals Residual-guided In-loop Filter Using Convolution Neural Network

2021 ◽  
Vol 17 (4) ◽  
pp. 1-19
Author(s):  
Wei Jia ◽  
Li Li ◽  
Zhu Li ◽  
Xiang Zhang ◽  
Shan Liu
Keyword(s):  
Neural Network ◽  
Video Coding ◽  
High Efficiency ◽  
Video Frame ◽  
High Efficiency Video Coding ◽  
Loop Filter ◽  
Video Codecs ◽  
Coding Efficiency ◽  
Residual Signal ◽  
The Rich

The block-based coding structure in the hybrid video coding framework inevitably introduces compression artifacts such as blocking, ringing, and so on. To compensate for those artifacts, extensive filtering techniques were proposed in the loop of video codecs, which are capable of boosting the subjective and objective qualities of reconstructed videos. Recently, neural network-based filters were presented with the power of deep learning from a large magnitude of data. Though the coding efficiency has been improved from traditional methods in High-Efficiency Video Coding (HEVC), the rich features and information generated by the compression pipeline have not been fully utilized in the design of neural networks. Therefore, in this article, we propose the Residual-Reconstruction-based Convolutional Neural Network (RRNet) to further improve the coding efficiency to its full extent, where the compression features induced from bitstream in form of prediction residual are fed into the network as an additional input to the reconstructed frame. In essence, the residual signal can provide valuable information about block partitions and can aid reconstruction of edge and texture regions in a picture. Thus, more adaptive parameters can be trained to handle different texture characteristics. The experimental results show that our proposed RRNet approach presents significant BD-rate savings compared to HEVC and the state-of-the-art CNN-based schemes, indicating that residual signal plays a significant role in enhancing video frame reconstruction.

scholarly journals Adaptive In-loop Filter Method for High-efficiency Video Coding

2011 ◽  
Vol 16 (1) ◽  
pp. 1-13
Author(s):  
Kwang-Su Jung ◽  
Jung-Hak Nam ◽  
Woong Lim ◽  
Hyun-Ho Jo ◽  
Dong-Gyu Sim ◽  
...  
Keyword(s):  
Video Coding ◽  
High Efficiency ◽  
Filter Method ◽  
High Efficiency Video Coding ◽  
Loop Filter

High-Performance Hardware Interpolation Architecture for High Efficiency Video Coding Decoder

2016 ◽  
Vol 11 (9) ◽  
pp. 764
Author(s):  
Lella Aicha Ayadi ◽  
Nihel Neji ◽  
Hassen Loukil ◽  
Mouhamed Ali Ben Ayed ◽  
Nouri Masmoudi
Keyword(s):  
Video Coding ◽  
High Performance ◽  
High Efficiency ◽  
High Efficiency Video Coding

scholarly journals A low-area high-efficiency video coding inverse transform core using resource and time sharing architecture

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Yuan-Ho Chen ◽  
Chieh-Yang Liu
Keyword(s):  
Video Coding ◽  
Large Scale ◽  
High Efficiency ◽  
Vlsi Design ◽  
Cmos Technology ◽  
Oxide Semiconductor ◽  
Time Sharing ◽  
High Efficiency Video Coding ◽  
Low Area ◽  
Matrix Products

AbstractIn this paper, a very-large-scale integration (VLSI) design that can support high-efficiency video coding inverse discrete cosine transform (IDCT) for multiple transform sizes is proposed. The proposed two-dimensional (2-D) IDCT is implemented at a low area by using a single one-dimensional (1-D) IDCT core with a transpose memory. The proposed 1-D IDCT core decomposes a 32-point transform into 16-, 8-, and 4-point matrix products according to the symmetric property of the transform coefficient. Moreover, we use the shift-and-add unit to share hardware resources between multiple transform dimension matrix products. The 1-D IDCT core can simultaneously calculate the first- and second-dimensional data. The results indicate that the proposed 2-D IDCT core has a throughput rate of 250 MP/s, with only 110 K gate counts when implemented into the Taiwan semiconductor manufacturing (TSMC) 90-nm complementary metal-oxide-semiconductor (CMOS) technology. The results show the proposed circuit has the smallest area supporting the multiple transform sizes.

Sign in / Sign up

Export Citation Format

Share Document