Maria Taipliadou | National and Kapodistrian University of Athens (original) (raw)
Uploads
Papers by Maria Taipliadou
CERN European Organization for Nuclear Research - Zenodo, Sep 28, 2022
Nowadays, multispectral and hyperspectral imaging is a key remote sensing technology used in Eart... more Nowadays, multispectral and hyperspectral imaging is a key remote sensing technology used in Earth observation missions for commercial, scientific and defense/security applications. The explosive growth in hyperspectral image data volume and instrument data rates, compete with limited available on-board storage resources and downlink bandwidth, making hyperspectral and multispectral image data compression a mission critical task. Lossy compression allows to achieve significant compression gains as a tradeoff to some distortion between the reconstructed and the original image. The CCSDS-122.1-B-1 Recommended standard, extends CCSDS 122.0-B-2 standard for compression of monoband two-dimensional (2D) images by providing an effective method of encoding multispectral and hyperspectral image data, specifying certain spectral transforms to exploit the similarities between the spectral bands, creating a transformed image that it is more efficiently compressed by the 2D encoders. In this paper, we introduce a hardware architecture and implementation of the CCSDS 122.1 standard. The introduced hardware architecture was described in VHDL and implemented, validated and demonstrated on a commercially available Zynq-7000 SoC ZC706 Evaluation Kit development board hosting a Xilinx XC7Z045 SRAM FPGA achieving a throughput performance of 1.5 Gbps. To the best of our knowledge, this is the first hardware implementation of CCSDS 122.1-B-1 Recommended standard in the open literature, thus offering a hardware-accelerated solution for transformed-based lossy multispectral and hyperspectral image compression.
CERN European Organization for Nuclear Research - Zenodo, Sep 28, 2022
Nowadays, multispectral and hyperspectral imaging is a key remote sensing technology used in Eart... more Nowadays, multispectral and hyperspectral imaging is a key remote sensing technology used in Earth observation missions for commercial, scientific and defense/security applications. The explosive growth in hyperspectral image data volume and instrument data rates, compete with limited available on-board storage resources and downlink bandwidth, making hyperspectral and multispectral image data compression a mission critical task. Lossy compression allows to achieve significant compression gains as a tradeoff to some distortion between the reconstructed and the original image. The CCSDS-122.1-B-1 Recommended standard, extends CCSDS 122.0-B-2 standard for compression of monoband two-dimensional (2D) images by providing an effective method of encoding multispectral and hyperspectral image data, specifying certain spectral transforms to exploit the similarities between the spectral bands, creating a transformed image that it is more efficiently compressed by the 2D encoders. In this paper, we introduce a hardware architecture and implementation of the CCSDS 122.1 standard. The introduced hardware architecture was described in VHDL and implemented, validated and demonstrated on a commercially available Zynq-7000 SoC ZC706 Evaluation Kit development board hosting a Xilinx XC7Z045 SRAM FPGA achieving a throughput performance of 1.5 Gbps. To the best of our knowledge, this is the first hardware implementation of CCSDS 122.1-B-1 Recommended standard in the open literature, thus offering a hardware-accelerated solution for transformed-based lossy multispectral and hyperspectral image compression.