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1.深圳技术大学 新材料与新能源学院,广东 深圳 518118
2.深圳大学 物理与光电工程学院,广东 深圳 518052
[ "吕德远(1995-),男,山东聊城人,硕士研究生,2018年于长春理工大学获得学士学位,现为深圳大学物理与光电工程学院硕士研究生,主要从事嵌入式系统、高光谱图像处理等方面的研究。E-mail:lvdeyuan@outlook.com" ]
[ "赵志刚(1977-),男,湖北黄冈人,博士、副教授、硕士生导师,1999年、2005年于军械工程学院(现陆军工程大学)分别获得学士、硕士学位,2010年于华中科技大学获得博士学位,现为深圳技术大学新材料与新能源学院副教授,主要从事微型高光谱成像、实时高光谱物质分类等方面的研究。E-mail: zhaozhigang@sztu.edu.cn" ]
收稿日期:2021-04-26,
修回日期:2021-06-06,
纸质出版日期:2022-04-25
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吕德远,黄浩文,曾珉等.快照马赛克高光谱图像CCSDS压缩器的FPGA实现[J].光学精密工程,2022,30(08):883-893.
LV Deyuan,HUANG Haowen,ZENG Min,et al.FPGA implementation of CCSDS compressor for snapshot mosaic hyperspectral images[J].Optics and Precision Engineering,2022,30(08):883-893.
吕德远,黄浩文,曾珉等.快照马赛克高光谱图像CCSDS压缩器的FPGA实现[J].光学精密工程,2022,30(08):883-893. DOI: 10.37188/OPE.20223008.0883.
LV Deyuan,HUANG Haowen,ZENG Min,et al.FPGA implementation of CCSDS compressor for snapshot mosaic hyperspectral images[J].Optics and Precision Engineering,2022,30(08):883-893. DOI: 10.37188/OPE.20223008.0883.
为解决快照马赛克高光谱图像数据量大、对传输带宽要求高的问题,采用最新的CCSDS 123.0-B-2多光谱/高光谱无损和近无损压缩国际标准,实现了基于FPGA的快照马赛克高光谱图像无损和近无损压缩。通过改进BIP(Band-Interleaved Pixels)排序算法,使每个时钟周期能够动态处理一个快照马赛克高光谱样本,数据吞吐率约提高至11倍,有效解决了该国际标准在快照马赛克高光谱图像压缩FPGA硬件实现时存在的流水线和并行化处理困难、处理速度慢的问题。实验结果表明,所实现的压缩器在Xilinx XC7Z020CLG-4平台上布局布线后FPGA整体逻辑资源占用率小于10%,100 MHz系统时钟下约22 ms即可完成一张高光谱图像的压缩,无损压缩性能在2.66~4.30 bits/samples之间,近无损压缩性能在1.01~3.70 bits/samples之间,能够满足快照马赛克高光谱成像技术在无线手持及无人机载领域的应用需求。
To solve the problem of large data volume and high transmission bandwidth requirement of snapshot mosaic hyperspectral images, the latest CCSDS 123.0-B-2 multispectral/hyperspectral lossless and near-lossless compression international standard is adopted to realize the FPGA-based lossless and near-lossless compression of snapshot mosaic hyperspectral images. By improving the BIP (Band-Interleaved Pixels) sequencing algorithm, a snapshot mosaic hyperspectral sample can be dynamically processed per clock cycle to 11 times higher of data throughput, and the problems of pipelining and parallelization difficulties and slow processing speed in the FPGA hardware implementation of snapshot mosaic hyperspectral image compression of this international standard have been effectively solved. The experimental results show that the overall logic resource usage of the implemented compressor is less than 10% after the layout and wiring of the FPGA on Xilinx XC7Z020CLG-4 platform, and the compression of a hyperspectral image can be completed in about 22 ms under 100 MHz system clock, with lossless compression performance between 2.66~4.30 bits/samples and the performance near-lossless compression is between 1.01~3.70 bits/samples, which can meet the application requirements of snapshot mosaic hyperspectral imaging technology in wireless handheld and unmanned airborne fields.
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