图像压缩信号数据的位组建模

J. Vaisey, Mark Trumbo
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引用次数: 0

摘要

只提供摘要形式。二进制可变顺序自适应算法,如Rissanen的UMC(1986)和JBIG,可用于无损压缩非二进制数据,将数据分成平面,每个平面为1位分辨率,并将每个平面传递给算法的单独实例。以这种方式运行的UMC算法是作者所知道的最强大的无损信号数据压缩器。我们试图理解为什么这种方法如此有效。我们研究了在将数据分割成单位平面并传递给建模器和编码器之前对数据进行灰色编码的常用技术,并将其与简单的加权二进制编码进行比较。然后,我们提出了一种非二进制伪格雷码作为生成分辨率大于或等于1位的平面的方法,并将其与其他传统方法进行了比较。生成伪格雷码的算法与构造二进制格雷码的算法非常相似,不同之处在于,我们不是最小化相邻位平面之间的汉明距离,而是最小化相邻位平面组之间的欧几里得距离。
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Bitgroup modeling of signal data for image compression
Summary form only given. Binary variable order adaptive algorithms like the UMC of Rissanen (1986) and JBIG can be used to losslessly compress non-binary data by splitting the data into planes, each of 1 bit resolution, and passing each plane to a separate instance of the algorithm. The UMC algorithm operated in this way is the most powerful lossless signal data compressor the authors are aware of. We attempt to develop an understanding of why this approach is so effective. We investigate the common technique of Gray coding the data before splitting it into single-bit planes and passing to the modeler and coder, and compare it to a simple weighted binary coding. We then propose a non-binary pseudo-Gray code as a method of generating planes of resolution greater than or equal to 1 bit, and compare it with the other conventional methods. The algorithm to generate the pseudo-Gray code is much the same as that for the construction of a binary Gray code, except that instead of minimizing the Hamming distance between neighboring bit planes, we instead minimize the Euclidean distance between adjacent groups of bit planes.
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