The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B3-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 755–762, 2021
https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-755-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 755–762, 2021
https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-755-2021

  29 Jun 2021

29 Jun 2021

ONBOARD/ON-GROUND IMAGE PROCESSING CHAIN FOR HIGH-RESOLUTION EARTH OBSERVATION SATELLITES

E. Cucchetti, C. Latry, G. Blanchet, J.-M. Delvit, and M. Bruno E. Cucchetti et al.
  • Centre National d’Etudes Spatiales - CST, 18 Av. Edouard Belin, 31000 France

Keywords: Compression, Denoising, Image processing chain, Remote Sensing, Restoration

Abstract. Over the last decade, the French space agency (CNES) has designed and successfully operated high-resolution satellites such as Pléiades. High-resolution satellites typically acquire panchromatic images with fine spatial resolutions and multispectral images with coarser samplings for downlink constraints. The multispectral image is reconstructed on the ground, using pan-sharpening techniques. Onboard compression and ground processing affect however the quality of the final product. In this paper, we describe our next-generation onboard/on-ground image processing chain for high-resolution satellites. This paper focuses on onboard compression, compression artefacts correction, denoising, deconvolution and pan-sharpening. In the first part, we detail our fixed-quality compression approach, which limits compression effects to a fraction of the noise, thus preserving the useful information in an image. This approach optimises the bitrate at the cost of image size, which depends on the scene complexity. This technique requires however pre- and post-processing steps. The noisy HR images obtained after decompression are suited for non-local denoising algorithms. We show in the second part of this paper that non-local denoising outperforms previous techniques by 15% in terms of root mean-squared error when tested on simulated noiseless references. Deconvolution is also detailed. In the final part of this paper, we put forward an adaptation of this chain to low-cost CMOS Bayer colour matrices. We demonstrate that the concept of our image chain remains valid, provided slight modifications (in particular dedicated transformations of the colour planes and demosaicing). A similar chain is under investigation for future missions.