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Performance analysis of medical image compression techniques

机译:医学图像压缩技术的性能分析

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Image compression has become one of the most important disciplines in digital electronics because of the ever growing popularity and usage of the internet and multimedia systems combined with the high requirements of the bandwidth and storage space. The increasing volume of data generated by some medical imaging modalities which justifies the use of different compression techniques to decrease the storage space and efficiency of transfer the images over the network for access to electronic patient records. This paper addresses the area of data compression as it is applicable to image processing. Here we are presented an effective algorithm to compress and to reconstruct digital imaging and communications in medicine (DICOM) images. Various image compression algorithms exist in today's commercial market. This paper outlines the comparison of compression methods such as JEPG, JEPG 2000 with SPIHT encoding on the basis of compression ratio and compression quality. The comparison of these compression methods are classified according to different medical images like MRI and CT. For JPEG based image compression RLE and Huffman encoding techniques are used by varying the bits per pixel. For JPEG 2000 based image compression SPIHT encoding method is used. The DCT and DWT methods are compared by varying bits per pixel and measured the performance parameters of MSE, PSNR and compression ratio. In JPEG 2000 method, compared the different wavelets like Haar, CDF 9/7, CDF 5/3 etc. and evaluated the compression ratio and compression quality. Also varied the decomposition levels of wavelet transform with different images.
机译:由于互联网和多媒体系统的日益普及和使用以及对带宽和存储空间的高要求,图像压缩已成为数字电子领域最重要的学科之一。由某些医学成像模态生成的数据量不断增加,这证明了使用不同压缩技术来减少存储空间和降低通过网络传输图像以访问电子病历的效率。本文探讨了数据压缩领域,因为它适用于图像处理。在这里,我们提出了一种有效的算法来压缩和重建医学中的数字成像和通信(DICOM)图像。在当今的商业市场中存在各种图像压缩算法。本文概述了基于压缩率和压缩质量的压缩方法(如JEPG,JEPG 2000和SPIHT编码)的比较。这些压缩方法的比较根据MRI和CT等不同的医学图像进行分类。对于基于JPEG的图像压缩,通过改变每个像素的位来使用RLE和霍夫曼编码技术。对于基于JPEG 2000的图像压缩,使用SPIHT编码方法。通过改变每个像素的比特来比较DCT和DWT方法,并测量MSE,PSNR和压缩率的性能参数。在JPEG 2000方法中,比较了Haar,CDF 9/7,CDF 5/3等不同的小波,并评估了压缩率和压缩质量。还改变了具有不同图像的小波变换的分解水平。

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