Adaptive Scalable Video Coding: An HEVC-Based Framework Combining the Predictive and Distributed Paradigms

HoangVan, Xiem; Ascenso, João; Pereira, Fernando

doi:10.1109/tcsvt.2016.2543120

Cited by 13 publications

(3 citation statements)

References 29 publications

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“…Zhang and Huo proposed a multimedia enhancement technique with quantum chaotic graph, which encrypted the image and improved the reliability and security of multimedia images [2]. To achieve the best multimedia enhancement layer compression efficiency, Hoangvan et al proposed a novel HEVC-based framework with high-quality scalability [3]. Ahmed et al proposed a method for multisaliency enhancement for multimedia image location estimation, which was mainly performed by mean-shift clustering of visual words and saliency maps of images [4].…”

Section: Introductionmentioning

confidence: 99%

Application of Image Processing Variation Model Based on Network Control Robot Image Transmission and Processing System in Multimedia Enhancement Technology

2022

Journal of Robotics

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The rapid development of the information age brings convenience to human life, but it also brings great challenges to information processing technology. Multimedia enhancement technology is an organic combination of multimedia technology and information processing technology, and it is also an important way of modern multimedia image information processing. However, its usefulness and effectiveness are increasingly negatively affected by the open information environment. The processing effect is also unable to meet the development requirements of the visual field. In order to improve this problem, this paper studied the image transmission and processing system of network-controlled robot on the basis of analyzing the characteristics of the problems existing in the current stage of multimedia technology. On this basis, a new image processing variational model was established and applied to multimedia enhancement technology, which improved the efficiency and effect of image information processing. Finally, the feasibility of its application function and performance was tested by experiments. The test results showed that in the difficult mode of the image processing task, the refresh time of the model in this paper in the multimedia enhancement technology was 1.13 s in total, which was not much different from the test results in the easy mode. Also, in the load stress test, the comprehensive test values under full-function operation and partial-function operation were 42.04% and 20.92%, respectively. Compared with the traditional model, the model in this paper has stronger carrying capacity in multimedia enhancement technology and has better processing ability and stability.

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Section: Introductionmentioning

confidence: 99%

Application of Image Processing Variation Model Based on Network Control Robot Image Transmission and Processing System in Multimedia Enhancement Technology

2022

Journal of Robotics

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“…Study towards adaptive encoding system is carried out by Van et al [55] where an integration of the distributed as well as predictive scheme of coding is introduced. The authors have presented the solution towards the complexity of the video coding system using two discrete approaches.…”

Section: Fig5 Structure For Partitioning Screen Contents [54]mentioning

confidence: 99%

Insights on Video Compression Strategies using Machine Learning

Rao

2019

IJEAT

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With the rising advancement of the multimedia technology, video compression is becoming a challenging problem. Although, there is availability of various standard compression algorithms, yet robust compression performance is yet to be seen in existing compression techniques. This paper also highlights that machine learning plays a significant contributory role in improving the performance of the video compression. Therefore, this manuscript offers a technical insight about the performance of existing video compression technique using machine learning approach. The contribution of this paper is its findings which states that machine learning approach do have significant advantage but the advantageous features are limited by the inherent and unsolved research problem. The core findings of this paper are basically to highlight the strength and limitations of existing methods as well as to highlight the research gap in terms of open-end research problems which requires immediate attention.

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“…SVC has temporal, spatial, and quality scalability. Scalable High-Efficiency Video Coding (SHVC) not only supports temporal, spatial and quality, but supports hybrid scalability, depth of bit scalability and gamut scalability [1][2][3][4][5][6][7][8][9] . For the quality scalability, it mainly includes Coarse Granular Scalable (CGS) [10][11] , Medium Granular Scalability (MGS) [12] , Fine Granular Scalable (FGS) [13][14] .…”

Section: Introductionmentioning

confidence: 99%

Quality Scalable Video Coding Algorithm Based on Pattern Recognition

Zhang¹,

Ai²,

Li³

2018

dtcse

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A novel quality scalable video coding algorithm based on pattern recognition was proposed in this paper. The self-organizing map (SOM) was used for scalable video coding. A coarse pattern library and two fine pattern libraries were designed for the base layer coding and the enhancement layer coding, respectively. Experimental results show that the peak signal to noise ratio (PSNR) improvement of reconstructed video images is 1.06dB when the compression ratio is 100:1.

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Adaptive Scalable Video Coding: An HEVC-Based Framework Combining the Predictive and Distributed Paradigms

Cited by 13 publications

References 29 publications

Application of Image Processing Variation Model Based on Network Control Robot Image Transmission and Processing System in Multimedia Enhancement Technology

Application of Image Processing Variation Model Based on Network Control Robot Image Transmission and Processing System in Multimedia Enhancement Technology

Insights on Video Compression Strategies using Machine Learning

Quality Scalable Video Coding Algorithm Based on Pattern Recognition

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