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An efficient block based lossless compression of medical images

机译:基于有效块的医学图像无损压缩

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摘要

Medical images play a significant role in diagnosis of diseases and require a simple and efficient compression technique. This paper proposes a block based lossless image compression algorithm using Hadamard transform and Huffman encoding which is a simple algorithm with less complexity. Initially input image is decomposed by Integer wavelet transform (IWT) and LL sub band is transformed by lossless Hadamard transformation (LHT) to eliminate the correlation inside the block. Further DC prediction (DCP) is used to remove correlation between adjacent blocks. The non-LL sub bands are validated for Non-transformed block (NTB) based on threshold. The main significance of this method is it proposes simple DCP, effective NTB validation and truncation. Based on the result of NTB, encoding is done either directly or after transformation by LHT and truncated. Finally all coefficients are encoded using Huffman encoder to compress. From the simulation results, it is observed that the proposed algorithm yields better results in terms of compression ratio when compared with existing lossless compression algorithms such as JPEG 2000. Most importantly the algorithm is tested with standard non medical images and set of medical images and provides optimum values of compression ratio and is quite efficient. (C) 2015 Elsevier GmbH. All rights reserved.
机译:医学图像在疾病诊断中起着重要作用,需要简单有效的压缩技术。提出了一种使用Hadamard变换和Huffman编码的基于块的无损图像压缩算法,该算法是一种简单,复杂度较低的算法。最初,输入图像通过整数小波变换(IWT)进行分解,LL子带通过无损Hadamard变换(LHT)进行变换,以消除块内的相关性。进一步的DC预测(DCP)被用于去除相邻块之间的相关性。基于阈值针对非变换块(NTB)验证非LL子带。该方法的主要意义在于它提出了简单的DCP,有效的NTB验证和截断。根据NTB的结果,编码可以直接进行,也可以通过LHT转换并截断后进行。最后,使用霍夫曼编码器对所有系数进行编码以进行压缩。从仿真结果可以看出,与现有的无损压缩算法(例如JPEG 2000)相比,该算法在压缩率方面产生了更好的结果。最重要的是,该算法已通过标准非医学图像和医学图像集进行了测试,并提供压缩率的最佳值,并且非常有效。 (C)2015 Elsevier GmbH。版权所有。

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