학술논문

Real - Time Applications of Video Compression in the Field of Medical Environments
Document Type
Conference
Source
2023 10th International Conference on Computing for Sustainable Global Development (INDIACom) Computing for Sustainable Global Development (INDIACom), 2023 10th International Conference on. :708-711 Mar, 2023
Subject
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Films
Video sequences
Redundancy
Transform coding
Video compression
Control systems
Encoding
Deep Convolutional Neural Networks
Deep Recurrent Auto Encoders
Video
Decoding
Deep learning
medical field
Language
Abstract
We introduce DCNN and DRAE appraoches for compression of medical videos, to decrease file size and storage requirements, there is an increasing need for medical video compression nowadays. Using a lossy compression technique, a higher compression ratio can be attained, but information will be lost, and possible diagnostic mistakes may follow. The requirement to store medical video in lossless format results from this. The aim of utilizing a lossless compression tool is to maximize compression because the traditional lossless compression technique yields a poor compression ratio. The temporal and spatial redundancy seen in video sequences can be successfully utilized by the proposed DCNN and DRAE encoding. This paper describes the lossless encoding mode and shows how a better compression ratio can be achieved.