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High level modular implementation of a lossy hyperspectral image compression algorithm on a FPGA

机译:FPGA上有损高光谱图像压缩算法的高电平模块化实现

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In this paper, a Field Programmable Gate Array (FPGA) implementation of the LCE (Lossy Compression for ExoMars) algorithm is presented. This algorithm shows a good quality/compression ratio tradeoff for hyperspectral images, at the expenses of a higher complexity with respect to lossless algorithms. In order to deal with this complexity levels, high level synthesis (HLS) tools, such as Catapult C, have been used together with Precision RTL so that a final implementation was obtained in a Virtex-5 FPGA. The results show a performance slightly higher than a previous lossless/near-lossless algorithm implementation, in terms of operating frequency (87 MHz vs. 81 MHz), with a reduced number of memory blocks, at the expenses of an increase in the number of digital signal processing (DSP) slices used.
机译:在本文中,介绍了LCE的现场可编程门阵列(FPGA)实现(exoMars的损耗压缩)算法。该算法显示了高光谱图像的良好质量/压缩比权衡,在相对于无损算法的较高复杂度的费用中。为了处理这种复杂程度,高级合成(HLS)工具,例如CataPult C,已经与精密RTL一起使用,以便在Virtex-5 FPGA中获得最终实现。结果表明,在运行频率(87 MHz与81 MHz)方面,在运行频率(87 MHz与81 MHz)方面的性能略高于先前的无损/近无损算法实现,其数量减少了数量的内存块。使用数字信号处理(DSP)切片。

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