A Block-Based Arithmetic Entropy Encoding Scheme for Medical Images

Urvashi Sharma, Meenakshi Sood, Emjee Puthooran, Yugal Kumar

Source Title: Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention

ISBN13: 9781668475447|ISBN10: 1668475448|EISBN13: 9781668475454

DOI: 10.4018/978-1-6684-7544-7.ch012

MLA

Sharma, Urvashi, et al. "A Block-Based Arithmetic Entropy Encoding Scheme for Medical Images." Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention, edited by Information Resources Management Association, IGI Global, 2023, pp. 190-206. https://doi.org/10.4018/978-1-6684-7544-7.ch012

APA

Sharma, U., Sood, M., Puthooran, E., & Kumar, Y. (2023). A Block-Based Arithmetic Entropy Encoding Scheme for Medical Images. In I. Management Association (Ed.), Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention (pp. 190-206). IGI Global. https://doi.org/10.4018/978-1-6684-7544-7.ch012

Chicago

Sharma, Urvashi, et al. "A Block-Based Arithmetic Entropy Encoding Scheme for Medical Images." In Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention, edited by Information Resources Management Association, 190-206. Hershey, PA: IGI Global, 2023. https://doi.org/10.4018/978-1-6684-7544-7.ch012

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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.