A Block-Based Arithmetic Entropy Encoding Scheme for Medical Images

Urvashi Sharma, Meenakshi Sood, Emjee Puthooran and Yugal Kumar
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Urvashi Sharma: Jaypee University of Information Technology, India
Meenakshi Sood: National Institute of Technical Teachers Training and Research, India
Emjee Puthooran: Jaypee University of Information Technology, India
Yugal Kumar: Jaypee University of Information Technology, India

International Journal of Healthcare Information Systems and Informatics (IJHISI), 2020, vol. 15, issue 3, 65-81

Abstract: The digitization of human body, especially for treatment of diseases can generate a large volume of data. This generated medical data has a large resolution and bit depth. In the field of medical diagnosis, lossless compression techniques are widely adopted for the efficient archiving and transmission of medical images. This article presents an efficient coding solution based on a predictive coding technique. The proposed technique consists of Resolution Independent Gradient Edge Predictor16 (RIGED16) and Block Based Arithmetic Encoding (BAAE). The objective of this technique is to find universal threshold values for prediction and provide an optimum block size for encoding. The validity of the proposed technique is tested on some real images as well as standard images. The simulation results of the proposed technique are compared with some well-known and existing compression techniques. It is revealed that proposed technique gives a higher coding efficiency rate compared to other techniques.

Date: 2020
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