Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/8325
Title: A Block-Based Arithmetic Entropy Encoding Scheme for Medical Images
Authors: Sharma, Urvashi
Sood, Meenakshi
Puthooran, Emjee
Kumar, Yugal
Keywords: Lossless compression
Gradient edge detection
Data compression
Issue Date: 2020
Publisher: Jaypee University of Information Technology, Solan, H.P.
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.
URI: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/8325
Appears in Collections:Journal Articles

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