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A novel medical image compression using Ripplet transform

机译:使用Ripplet变换的新型医学图像压缩

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摘要

In spite of great advancements in multimedia data storage and communication technologies, compression of medical data remains challenging. This paper presents a novel compression method for the compression of medical images. The proposed method uses Ripplet transform to represent singularities along arbitrarily shaped curves and Set Partitioning in Hierarchical Trees encoder to encode the significant coefficients. The main objective of the proposed method is to provide high quality compressed images by representing images at different scales and directions and to achieve high compression ratio. Experimental results obtained on a set of medical images demonstrate that besides providing multiresolution and high directionality, the proposed method attains high Peak Signal to Noise Ratio and significant compression ratio as compared with conventional and state-of-art compression methods.
机译:尽管多媒体数据存储和通信技术取得了巨大进步,但医疗数据的压缩仍然具有挑战性。本文提出了一种新颖的医学图像压缩方法。所提出的方法使用Ripplet变换来表示沿任意形状曲线的奇异性,并使用“层次树”编码器中的“设置分区”对有效系数进行编码。所提出的方法的主要目的是通过以不同比例和方向表示图像来提供高质量的压缩图像,并实现高压缩率。在一组医学图像上获得的实验结果表明,与传统的和最新的压缩方法相比,该方法除了提供多分辨率和高方向性之外,还具有较高的峰值信噪比和显着的压缩率。

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