A Block-Based Arithmetic Entropy Encoding Scheme for Medical Images

Urvashi Sharma, M. Sood, Emjee Puthooran, Y. Kumar
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引用次数: 4

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.
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一种基于分块的医学图像算术熵编码方案
人体的数字化,尤其是疾病治疗的数字化,可以产生大量的数据。生成的医疗数据具有很大的分辨率和位深度。在医学诊断领域,无损压缩技术被广泛应用于医学图像的高效存档和传输。本文提出了一种基于预测编码技术的高效编码方案。该技术包括分辨率无关梯度边缘预测器(RIGED16)和基于块的算术编码(BAAE)。该技术的目标是找到用于预测的通用阈值,并提供用于编码的最佳块大小。在一些真实图像和标准图像上验证了该方法的有效性。仿真结果与一些已知的和现有的压缩技术进行了比较。结果表明,与其他编码技术相比,该技术具有更高的编码效率。
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