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Faster Image Compression Technique Based on LZW Algorithm Using GPU Parallel Processing

机译:基于LZW算法的GPU并行处理更快的图像压缩技术

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摘要

As web, mobile, desktop and all other applications use image for different purposes, image compression technique has become one of the most important applications in image analysis as well as in computer science. Though image compression is an old concept, it is still a very time-consuming process which has opened a new field of research in image compression. In this paper, we showcase our extensive research works performed on LZW (Lempel-Ziv-Welch) algorithm, a lossless image compression algorithm that yields faster computation time when it is processed with parallel computation, based on the outcome of our research. The improved time efficiency obtained from our experimental result can be perceived in the context of millisecond scale rather than in the macro level of measurement along with keeping the decoded image in lossless format.
机译:随着Web,移动,桌面和所有其他应用程序出于不同目的使用图像,图像压缩技术已成为图像分析以及计算机科学中最重要的应用程序之一。尽管图像压缩是一个古老的概念,但它仍然是一个非常耗时的过程,为图像压缩开辟了一个新的研究领域。在本文中,我们将展示我们在LZW(Lempel-Ziv-Welch)算法上进行的广泛研究工作,LZW是一种无损图像压缩算法,根据我们的研究结果,该算法在使用并行计算进行处理时可缩短计算时间。从我们的实验结果中获得的改进的时间效率可以在毫秒级的范围内而不是在宏测量级别上感知,并且可以将解码图像保持在无损格式。

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