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首页> 外文期刊>Journal of visual communication & image representation >Grayscale true two-dimensional dictionary-based image compression
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Grayscale true two-dimensional dictionary-based image compression

机译：基于灰度真二维字典的图像压缩

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摘要

Dictionary-based encoding methods are popular forms of data compression. These methods were initially implemented to reduce the one-dimensional correlation in data, since they are designed to compress text. Therefore, they do not take advantage of the fact that adjacent pixels in images are correlated in two dimensions. Previous attempts have been made to adapt dictionary-based compression schemes to consider the two-dimensional nature of images, but mostly for binary images. In this paper, a two-dimensional dictionary-based lossless image compression scheme for grayscale images is introduced. The proposed scheme reduces correlation in image data by finding two-dimensional blocks of pixels that are approximately matched throughout the data and replacing them with short codewords. Test results show that the compression performance of the proposed scheme outperforms and surpasses any other existing dictionary-based lossless compression scheme. The results also show that it slightly outperforms JPEG-2000s compression performance, when it operates in its lossless mode, and it is comparable to JPEG-LS's and CALIC's compression performance, where JPEG-2000 and JPEG-LS are the current image compression standards, and CALIC is a Context-based Adaptive Lossless Image Coding scheme.
机译：基于字典的编码方法是数据压缩的流行形式。最初实现这些方法是为了减少数据中的一维相关性，因为它们被设计为压缩文本。因此，它们没有利用图像中的相邻像素在二维上相关的事实。先前已经进行了尝试以使基于字典的压缩方案适应考虑图像的二维性质，但是主要针对二进制图像。本文介绍了一种基于二维字典的灰度图像无损图像压缩方案。所提出的方案通过找到在整个数据中近似匹配的二维像素块并将其替换为短码字来降低图像数据中的相关性。测试结果表明，该方案的压缩性能优于并超过了任何其他现有的基于字典的无损压缩方案。结果还表明，当它以无损模式运行时，它的性能略优于JPEG-2000的压缩性能，并且可以与JPEG-LS和CALIC的压缩性能相媲美，其中JPEG-2000和JPEG-LS是当前的图像压缩标准， CALIC是一种基于上下文的自适应无损图像编码方案。

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