JOURNAL ARTICLE

Adaptive Video Compression And Transmission Over Heterogeneous Networks

Miss. Kirti Lakapate*1, Prof. Mahesh Karanjkar2 & Prof. Namdev Pergad3

Year: 2018 Journal:   Zenodo (CERN European Organization for Nuclear Research)   Publisher: European Organization for Nuclear Research

Abstract

Video may go through different sorts of heterogeneous systems amid the procedure of transmission, which impacts affects the continuous video quality. The previous technique focus on how to compress videos based on the video flow without considering the real-time network information. This system presents an adaptive method that combines video transmission control and video encoding the system over heterogeneous networks. This system includes steps such as : first, to collect and standardize the real-time information describing the network and the video, then to assess the video quality and calculate the video coding rate based on the standardized information, and then to process the encoded compression of the video according to the calculated coding rate and transfer the compressed video. The aim of this project is to provide an adaptive video transmission control system and technique to enhance the ongoing video quality, which takes the continuous system data into the video transmission control over heterogeneous systems. The application-layer protocol has three phases: Simultaneously collect video and network flow status To adjust the parameters for video quality dynamically that, come from the network and video environment feedback. To optimize the video coding rate that is as per the present condition conditions.

Keywords:
Video compression picture types Video tracking Multiview Video Coding Data compression Video processing Scalable Video Coding Video quality Heterogeneous network Uncompressed video

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Topics

Video Coding and Compression Technologies
Physical Sciences →  Computer Science →  Signal Processing
Image and Video Quality Assessment
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Network Traffic and Congestion Control
Physical Sciences →  Computer Science →  Computer Networks and Communications

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