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Real - Time Applications of Video Compression in the Field of Medical Environments


Mr.K. Siva Kumar, Dr. P. Bindhu Madhavi, Dr.K. Janaki


Vol. 23  No. 11  pp. 73-76


We introduce DCNN and DRAE appraoches for compression of medical videos, in order 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 compression ratio greater than 2 (2:1) can be achieved.


Deep Convolutional Neural Networks, Deep Recurrent Auto Encoders, Video, Encoding, Decoding, Deep learning, medical field.