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N-Square Approach for the Erection of Redundancy Codes

机译:冗余码的N平方方法

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This paper addresses the area of data compression which is an application of image processing. There are several lossy and lossless coding techniques developed all through the last two decades. Although very high compression can be achieved with lossy compression techniques, they are deficient in obtaining the original image. While lossless compression technique recovers the image exactly. In applications related to medical imaging lossless techniques are required, as the loss of information is deplorable. The objective of image compression is to symbolize an image with a handful number of bits as possible while preserving the quality required for the given application. In this paper we are introducing a new lossless compression technique which even better reduces the entropy there by reducing the average number of bits with the utility of Non Binary Huffman coding through the use of N-Square approach. Our extensive experimental results demonstrate that the proposed scheme is very competitive and this addresses the limitations of D value in the existing system by proposing a pattern called N-Square approach for it. The newly proposed algorithm provides a good means for lossless image compression.
机译:本文介绍了数据压缩领域,它是图像处理的一种应用。在过去的二十年中,已经开发了几种有损和无损编码技术。尽管可以使用有损压缩技术来实现非常高的压缩率,但是它们在获取原始图像方面是有缺陷的。无损压缩技术可以准确地恢复图像。在与医学成像有关的应用中,需要无损技术,因为信息丢失是令人遗憾的。图像压缩的目的是在保持给定应用所需的质量的同时,以尽可能少的位数来符号化图像。在本文中,我们将介绍一种新的无损压缩技术,该技术通过使用N平方方法利用非二进制霍夫曼编码来减少平均比特数,从而更好地减少其中的熵。我们广泛的实验结果表明,所提出的方案具有很强的竞争力,并且通过提出一种称为N平方方法的模式来解决现有系统中D值的局限性。新提出的算法为无损图像压缩提供了很好的手段。

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