Presentation + Paper
29 September 2017 High efficient optical remote sensing images acquisition for nano-satellite−framework
Feng Li, Lei Xin, Yang Liu, Jie Fu, Yuhong Liu, Yi Guo
Author Affiliations +
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.
Conference Presentation
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Feng Li, Lei Xin, Yang Liu, Jie Fu, Yuhong Liu, and Yi Guo "High efficient optical remote sensing images acquisition for nano-satellite−framework", Proc. SPIE 10423, Sensors, Systems, and Next-Generation Satellites XXI, 104231Q (29 September 2017); https://doi.org/10.1117/12.2278171
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CITATIONS
Cited by 2 scholarly publications and 1 patent.
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KEYWORDS
Image compression

Image acquisition

Remote sensing

CMOS sensors

Image processing

CCD image sensors

Image quality

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