scholarly journals VLSI Architectures of a Wiener Filter for Video Coding

Electronics ◽  
2021 ◽  
Vol 10 (16) ◽  
pp. 1961
Author(s):  
Walid Walid ◽  
Giorgio Armanno ◽  
Sandro Di Paola ◽  
Massimo Ruo Roch ◽  
Guido Masera ◽  
...  
Keyword(s):  
Computational Complexity ◽  
Video Coding ◽  
Data Compression ◽  
Open Source ◽  
Processing Time ◽  
Wiener Filter ◽  
Memory Space ◽  
Vlsi Architectures ◽  
Modern Age ◽  
Efficient Data

In the modern age, the use of video has become fundamental in communication and this has led to its use through an increasing number of devices. The higher resolution required for images and videos leads to more memory space and more efficient data compression, obtained by improving video coding techniques. For this reason, the Alliance for Open Media (AOMedia) developed a new open-source and royalty-free codec, named AOMedia Video 1 (AV1). This work focuses on the Wiener filter, a specific loop restoration tool of the AV1 video coding format, which features a significant amount of computational complexity. A new hardware architecture implementing the separable symmetric normalized Wiener filter is presented. Furthermore, the paper details possible optimizations starting from the basic architecture. These optimizations allow the Wiener filter to achieve a 100× reduction in processing time, compared to existing works, and 5× improvement in megasamples per second.

scholarly journals An Overview of Watershed Algorithm Implementations in Open Source Libraries

2018 ◽  
Vol 4 (10) ◽  
pp. 123 ◽  
Author(s):  
Anton Kornilov ◽  
Ilia Safonov
Keyword(s):  
Open Source ◽  
Processing Time ◽  
Deep Understanding ◽  
Watershed Algorithm ◽  
Watershed Segmentation ◽  
Memory Consumption ◽  
3D Images ◽  
Memory Space ◽  
Volumetric Images ◽  
2D And 3D

Watershed is a widespread technique for image segmentation. Many researchers apply the method implemented in open source libraries without a deep understanding of its characteristics and limitations. In the review, we describe benchmarking outcomes of six open-source marker-controlled watershed implementations for the segmentation of 2D and 3D images. Even though the considered solutions are based on the same algorithm by flooding having O(n)computational complexity, these implementations have significantly different performance. In addition, building of watershed lines grows processing time. High memory consumption is one more bottleneck for dealing with huge volumetric images. Sometimes, the usage of more optimal software is capable of mitigating the issues with the long processing time and insufficient memory space. We assume parallel processing is capable of overcoming the current limitations. However, the development of concurrent approaches for the watershed segmentation remains a challenging problem.

Energy Efficient Data Compression in Cloud based IoT

2021 ◽  
pp. 1-1
Author(s):  
Halah Mohammed Al-Kadhim ◽  
Hamed S. Al-Raweshidy
Keyword(s):  
Data Compression ◽  
Energy Efficient ◽  
Efficient Data

A Unitary-UCA-Root-MUSIC Algorithm Based on MSWF

2014 ◽  
Vol 610 ◽  
pp. 339-344
Author(s):  
Qiang Guo ◽  
Yun Fei An
Keyword(s):  
Computer Simulation ◽  
Computational Complexity ◽  
Real Time ◽  
Unitary Transformation ◽  
Wiener Filter ◽  
Doa Estimation ◽  
Signal Subspace ◽  
Music Algorithm ◽  
Multi Stage ◽  
Simulation Results

A UCA-Root-MUSIC algorithm for direction-of-arrival (DOA) estimation is proposed in this paper which is based on UCA-RB-MUSIC [1]. The method utilizes not only a unitary transformation matrix different from UCA-RB-MUSIC but also the multi-stage Wiener filter (MSWF) to estimate the signal subspace and the number of sources, so that the new method has lower computational complexity and is more conducive to the real-time implementation. The computer simulation results demonstrate the improvement with the proposed method.

scholarly journals Texture Grouping and Statistical Optimization Based Mode Prediction Decision Algorithm for Fast HEVC Intra Coding

2021 ◽  
Author(s):  
Jianhua Wang ◽  
Feng Lin ◽  
Jing Zhao ◽  
Yongbing Long
Keyword(s):  
Computational Complexity ◽  
Video Coding ◽  
Rate Distortion ◽  
Statistical Optimization ◽  
Optimal Prediction ◽  
Statistical Probability ◽  
Decision Algorithm ◽  
Texture Information ◽  
Prediction Mode ◽  
Probability Optimization

Abstract HEVC (High Efficiency Video Coding), as one of the newest international video coding standard, can achieve about 50% bit rate reduction compared with H.264/AVC (Advanced Video Coding) at the same perceptual quality due to the use of flexible CTU(coding tree unit) structure, but at the same time, it also dramatically adds the higher computational complexity for HEVC. With the aim of reducing the computational complexity, a texture grouping and statistical optimization based mode prediction decision algorithm is proposed for HEVC intra coding in this paper. The contribution of this paper lies in the fact that we successfully use the texture information grouping and statistical probability optimization technology to rapidly determine the optimal prediction mode for the current PU, which can reduce many unnecessary prediction and calculation operations of HCost (Hadamard Cost) and RDCost (Rate Distortion Cost) in HEVC, thus saving much computation complexity for HEVC. Specially, in our scheme, firstly we group 35 intra prediction modes into 5 subsets of candidate modes list according to its texture information of edge in the current PU, and each subset only contains 11 intra prediction modes, which can greatly reduce many traversing number of candidate mode in RMD (Rough Mode Decision) from 35 to 11 prediction modes; Secondly we use the statistical probability of the first candidate modes in candidate modes list as well as MPM selected as the optimal prediction mode to reduce the number of candidate modes in RDO(Rate Distortion Optimization), which can reduce the number of candidate modes from 3+MPM or 8+MPM to 2 candidate modes; At last, we use the number of candidate modes determined above to quickly find the optimal prediction mode with the minimum RDCost by RDO process. As a result, the computational complexity of HEVC can be efficiently reduced by our proposed scheme. And the simulation results of our experiments show that our proposed intra mode prediction decision algorithm based on texture information grouping and statistical probability optimization in this paper can reduce about 46.13% computational complexity on average only at a cost of 0.67% bit rate increase and 0.056db PSNR decline compared with the standard reference HM16.1 algorithm.

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