Thematic data processing on board the satellite BIRD

Halle, Winfried; Venus, Holger; Skrbek, W.

doi:10.1117/12.406579

Cited by 8 publications

(3 citation statements)

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“…Finally, some designs involve processors ranging from highly specialised systems like the neural network processor NI1000 [Halle et al 2001] as part of BIRD's thematic onboard data processing experiment, to the 32-bit IDT R-3081 [Lovellette et al 2003]. …”

Section: Selected Commercial-off-the-shelf Processing Solutions On-bomentioning

confidence: 99%

Reliability through redundant parallelism for micro-satellite computing

McLoughlin

Bretschneider

2010

ACM Trans. Embed. Comput. Syst.

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Section: Selected Commercial-off-the-shelf Processing Solutions On-bomentioning

confidence: 99%

Reliability through redundant parallelism for micro-satellite computing

McLoughlin

Bretschneider

2010

ACM Trans. Embed. Comput. Syst.

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“…htm). Main on-board data processing capabilities are (1) a thematic on-board neural network classificator for disaster warning and monitoring; and (2) radiometric and geometric on-board correction of sensor signals (Halle et al, 2000;Gill et al, 2001). Some analysis and investigation for on-board data processing capabilities can be found in Zhou et al (2003;.…”

Section: On-board Image Processing Via Advanced Sensorsmentioning

confidence: 99%

Current status and future direction of sensors in Earth-observing satellites

Zhou

Wang

2003

SPIE Proceedings

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With the increasing sensor development, smart sensor, advanced sensor, and intelligent sensor, especially, distributed sensors, sensor network and sensor integration are being taken into account for application of our environmental monitoring and Earth source investigation. This paper investigates the development of sensors in Earth observing (EO) satellites, analyzes the current high-resolution EO satellites and presents the direction of new imaging systems in future Earth observing satellite. The purpose of this paper is to contribute to those who are interested in knowing and keeping track of the details of the imaging system of earth observing satellites.

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“…Through applying the characteristics of FPGA parallel computing, the proposed method by David and Don [23] improved the speed of image correction. Winfried et al [24] designed an on-board bispectral infrared detection (BIRD) system based on the neural network processor NI1000, a digital signal processor (DSP), and an FPGA. The system can perform on-board radiometric correction, geometric correction, and texture extraction.…”

Section: Introductionmentioning

confidence: 99%

On-Board Ortho-Rectification for Images Based on an FPGA

et al. 2017

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Abstract:The traditional ortho-rectification technique for remotely sensed (RS) images, which is performed on the basis of a ground image processing platform, has been unable to meet timeliness or near timeliness requirements. To solve this problem, this paper presents research on an ortho-rectification technique based on a field programmable gate array (FPGA) platform that can be implemented on board spacecraft for (near) real-time processing. The proposed FPGA-based ortho-rectification method contains three modules, i.e., a memory module, a coordinate transformation module (including the transformation from geodetic coordinates to photo coordinates, and the transformation from photo coordinates to scanning coordinates), and an interpolation module. Two datasets, aerial images located in central Denver, Colorado, USA, and an aerial image from the example dataset of ERDAS IMAGINE 9.2, are used to validate the processing speed and accuracy. Compared to traditional ortho-rectification technology, the throughput from the proposed FPGA-based platform and the personal computer (PC)-based platform are 11,182.3 kilopixels per second and 2582.9 kilopixels per second, respectively. This means that the proposed FPGA-based platform is 4.3 times faster than the PC-based platform for processing the same RS images. In addition, the root-mean-square errors of the planimetric coordinates ϕ X and ϕ Y and the distance ϕ S are 1.09 m, 1.61 m, and 1.93 m, respectively, which can meet the requirements of correction accuracy in practice.

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Thematic data processing on board the satellite BIRD

Cited by 8 publications

References 0 publications

Reliability through redundant parallelism for micro-satellite computing

Reliability through redundant parallelism for micro-satellite computing

Current status and future direction of sensors in Earth-observing satellites

On-Board Ortho-Rectification for Images Based on an FPGA

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