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24 August 2010 CNES studies for on-board implementation via HLS tools of a cloud-detection module for selective compression
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Abstract
Future CNES high resolution instruments for remote sensing missions will lead to higher data-rates because of the increase in resolution and dynamic range. For example, the ground resolution improvement has induced a data-rate multiplied by 8 from SPOT4 to SPOT5 [1] and by 28 to PLEIADES-HR [2]. Innovative "smart" compression techniques will be then required, performing different types of compression inside a scene, in order to reach higher global compression ratios while complying with image quality requirements. This socalled "selective compression", allows important compression gains by detecting and then differently compressing the regions-of-interest (ROI) and non-interest in the image (e.g. higher compression ratios are assigned to the non-interesting data). Given that most of CNES high resolution images are cloudy [1], significant mass-memory and transmission gain could be reached by just detecting and suppressing (or compressing significantly) the areas covered by clouds. Since 2007, CNES works on a cloud detection module [3] as a simplification for on-board implementation of an already existing module used on-ground for PLEIADES-HR album images [4]. The different steps of this Support Vector Machine classifier have already been analyzed, for simplification and optimization, during this on-board implementation study: reflectance computation, characteristics vector computation (based on multispectral criteria) and computation of the SVM output. In order to speed up the hardware design phase, a new approach based on HLS [5] tools is being tested for the VHDL description stage. The aim is to obtain a bit-true VDHL design directly from a high level description language as C or Matlab/Simulink [6].
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
R. Camarero, C. Thiebaut, Ph. Dejean, and A. Speciel "CNES studies for on-board implementation via HLS tools of a cloud-detection module for selective compression", Proc. SPIE 7810, Satellite Data Compression, Communications, and Processing VI, 781004 (24 August 2010); https://doi.org/10.1117/12.860140
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