High efficient optical remote sensing images acquisition for nano-satellite-framework

Feng Li, Lei Xin, Yang Liu, Jie Fu, Yuhong Liu, Yi Guo

Research output: Chapter in Book / Conference PaperConference Paperpeer-review

3 Citations (Scopus)

Abstract

It is more difficult and challenging to implement Nano-satellite (NanoSat) based optical Earth observation missions than conventional satellites because of the limitation of volume, weight and power consumption. In general, an image compression unit is a necessary onboard module to save data transmission bandwidth and disk space. The image compression unit can get rid of redundant information of those captured images. In this paper, a new image acquisition framework is proposed for NanoSat based optical Earth observation applications. The entire process of image acquisition and compression unit can be integrated in the photo detector array chip, that is, the output data of the chip is already compressed. That is to say, extra image compression unit is no longer needed; therefore, the power, volume, and weight of the common onboard image compression units consumed can be largely saved. The advantages of the proposed framework are: the image acquisition and image compression are combined into a single step; it can be easily built in CMOS architecture; quick view can be provided without reconstruction in the framework; Given a certain compression ratio, the reconstructed image quality is much better than those CS based methods. The framework holds promise to be widely used in the future.
Original languageEnglish
Title of host publicationProceedings of SPIE. Volume 10423: Sensors, Systems, and Next-Generation Satellites XXI, 11–14 September 2017, Warsaw, Poland
PublisherSPIE
Number of pages6
ISBN (Print)9781510613119
DOIs
Publication statusPublished - 2017
EventSensors_Systems_and Next-Generation Satellites (Conference) -
Duration: 11 Sept 2017 → …

Publication series

Name
ISSN (Print)0277-786X

Conference

ConferenceSensors_Systems_and Next-Generation Satellites (Conference)
Period11/09/17 → …

Keywords

  • image compression
  • image quality
  • nanosatellites
  • remote sensing

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