TRLE -一种用于并行体绘制系统图像合成的有效数据压缩方案

Ching-Feng Lin, Yeh-Ching Chung, Don-Lin Yang
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引用次数: 2

摘要

本文提出了一种有效的数据压缩方案——模板游程编码(TRLE)方案,用于并行体绘制系统的图像合成。给定2n/spl倍/2n像素的图像,在TRLE方案中,图像被处理为n/spl倍/n块,每个块有2/spl倍/2像素。由于像素可以是空白像素或非空白像素,因此一个块中有16个模板。为了压缩图像,TRLE方案使用模板逐行编码块。同一行中的块被编码为trle序列。通过将所有trle序列打包在一个包中,这个包就是可以在处理器之间发送/接收的压缩部分图像。为了评估TRLE方案的性能,我们将该方案与BR、RLE和BRLC方案进行了比较。由于数据压缩方案需要配合一些数据通信方案,在实现中采用了二进制交换(BS)、并行流水线(PP)和旋转平铺(RT)三种数据通信方案。通过将四种数据压缩方案与三种数据通信方案相结合,我们得到了12种图像合成方法。在PC机集群上实现了这12种方法,测量了数据计算时间和数据通信时间。实验结果表明,结合RT数据通信的TRLE数据压缩方案优于其他11种图像合成方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
TRLE - an efficient data compression scheme for image composition of parallel volume rendering systems
In this paper we present an efficient data compression scheme, the template run-length encoding (TRLE) scheme, for image composition of parallel volume rendering systems. Given an image with 2n/spl times/2n pixels, in the TRLE scheme, the image is treated as n/spl times/n blocks and each block has 2/spl times/2 pixels. Since a pixel can be a blank or non-blank pixel, there are 16 templates in a block. To compress an image, the TRLE scheme uses the templates to encode blocks row by row. Blocks in the same row are encoded as a TRLE-sequence. By packing all TRLE-sequences in a packet, the packet is the compressed partial image that can be sent/received among processors. To evaluate the performance of the TRLE scheme, we compare the proposed scheme with the BR, the RLE, and the BRLC schemes. Since a data compression scheme needs to cooperate with some data communication schemes, in the implementation, the binary-swap (BS), the parallel-pipelined (PP), and the rotate-tiling (RT) data communication schemes are used. By combining the four data compression schemes with the three data communication schemes, we have twelve image composition methods. These twelve methods are implemented on a PC cluster The data computation time and the data communication time are measured. The experimental results show that the TRLE data compression scheme with the RT data communication scheme outperforms other eleven image composition methods.
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