• Optics and Precision Engineering
  • Vol. 29, Issue 12, 2956 (2021)
Lei XIN1,*, Feng LI1, Xiao-tian LU1, Zhi-yi ZHAO1,2, and Ji-jin ZHAO3
Author Affiliations
  • 1Qian Xuesen Laboratory of Space Technology, China Academy of Space Technology, Beijing00094, China
  • 2School of Instrument Science and Opto Electronic Engineering, Beijing Information Science & Technology University, Beijing10019, China
  • 3Beijing Institute of Remote Sensing Information, Beijing100192, China
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    DOI: 10.37188/OPE.20212912.2956 Cite this Article
    Lei XIN, Feng LI, Xiao-tian LU, Zhi-yi ZHAO, Ji-jin ZHAO. Efficient coding and reconstruction for optical remote sensing images[J]. Optics and Precision Engineering, 2021, 29(12): 2956 Copy Citation Text show less

    Abstract

    Based on the theory of compressed sensing, a method for efficient coding and reconstruction of optical remote sensing images is proposed to reduce the pressure of data acquisition and transmission faced by large area scan cameras. First, a multi-domain perception matrix is constructed combining the spatial and compressed sensing domains. Compression is realized while sampling, and multiple compressed domain information is obtained. Then, for multi-domain compressed information, a reconstruction method based on the Huber function is proposed to rapidly reconstruct high fidelity images. The results of the optical image coding and reconstruction techniques proposed in this paper have higher structural similarity(SSIM) and PSNR compared to JPEG compression methods. Using images of the Jilin-1 satellite, single target and scene infrared images yields a PSNR reaching 40 dB and SSIM exceeding 0.8. Based on these findings, an efficient system for coding and restoring optical images is designed. The proposed system can meet the need for rapid compression and high fidelity reconstruction on the satellite.
    Lei XIN, Feng LI, Xiao-tian LU, Zhi-yi ZHAO, Ji-jin ZHAO. Efficient coding and reconstruction for optical remote sensing images[J]. Optics and Precision Engineering, 2021, 29(12): 2956
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