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首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing >An Extremely Pipelined FPGA Implementation of a Lossy Hyperspectral Image Compression Algorithm
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An Extremely Pipelined FPGA Implementation of a Lossy Hyperspectral Image Compression Algorithm

机译：一种极其流水线的FPGA实现的有损高光谱图像压缩算法

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摘要

Segmented and pipelined execution has been a staple of computing for the past decades. Operations over different values can be carried out at the same time speeding up computations. Hyperspectral image compression sequentially processes samples, exploiting local redundancies to generate a predictable data stream that can be compressed. In this article, we take advantage of a low complexity predictive lossy compression algorithm which can be executed over an extremely long pipeline of hundreds of stages. We can avoid most stalls and maintain throughput close to the theoretical maximum. The different steps operate over integers with simple arithmetic operations, so they are especially well-suited for our FPGA implementation. Results on a Virtex-7 show a maximum frequency of over 300 MHz for a throughput of over 290 MB/s, with a space-qualified Virtex-5 reaching 258 MHz, being five times as fast as the previous FPGA designs. This shows that a modular pipelined approach is beneficial for these kinds of compression algorithms.
机译：分段和流水线执行是过去几十年来计算的主食。可以在加速计算的同时执行对不同值的操作。高光谱图像压缩顺序地处理样本，利用本地冗余以生成可以压缩的可预测数据流。在本文中，我们利用了低复杂性预测损失压缩算法，该压缩算法可以在数百个阶段的极长管道上执行。我们可以避免大多数摊位并保持靠近理论最大值的吞吐量。不同的步骤通过简单的算术运算运行整数，因此它们特别适合我们的FPGA实现。 Virtex-7上的结果显示出超过390 MB / s的吞吐量超过300 MHz的最大频率，空间合格的Virtex-5达到258 MHz，速度为先前的FPGA设计的五倍。这表明模块化流水线方法是有益于这些类型的压缩算法。

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