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Adaptive Prediction Methods for Medical Image/Video compression for Telemedicine Application
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Author(s): Ketki C. Pathak (Sarvajanik College of Engineering and Technology, India), Jignesh N. Sarvaiya (Sardar Vallabhbhai National Institute of Technology Suart, India)and Anand D. Darji (Sardar Vallabhbhai National Institute of Technology Suart, India)
Copyright: 2019
Pages: 32
Source title:
Histopathological Image Analysis in Medical Decision Making
Source Author(s)/Editor(s): Nilanjan Dey (Techno India College of Technology, India), Amira S. Ashour (Tanta University, Egypt), Harihar Kalia (Seemantha Engineering College, India), R.T. Goswami (Techno India College of Technology, India)and Himansu Das (KIIT University, India)
DOI: 10.4018/978-1-5225-6316-7.ch011
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Abstract
Due to rapid development of multimedia communication and advancement of image acquisition process, there is a crucial requirement of high storage and compression techniques to mitigate high data rate with limited bandwidth scenario for telemedicine application. Lossless compression is one of the challenging tasks in applications like medical, space, and aerial imaging field. Apart from achieving high compression ratio, in these mentioned applications there is a need to maintain the original imaging quality along with fast and adequate processing. Predictive coding was introduced to remove spatial redundancy. The accuracy of predictive coding is based on the choice of effective and adaptive predictor which is responsible for removing spatial redundancy. Medical images like computed tomography (CT) and magnetic resonance imaging (MRI) consume huge storage and utilize maximum available bandwidth. To overcome these inherent challenges, the authors have reviewed various adaptive predictors and it has been compared with existing JPEG and JPEG LS-based linear prediction technique for medical images.
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