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Date of download: 6/18/2016 Copyright © 2016 SPIE. All rights reserved. Traditional camera-PC-based image processing system. Figure Legend: From: Simulation.

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Presentation on theme: "Date of download: 6/18/2016 Copyright © 2016 SPIE. All rights reserved. Traditional camera-PC-based image processing system. Figure Legend: From: Simulation."— Presentation transcript:

1 Date of download: 6/18/2016 Copyright © 2016 SPIE. All rights reserved. Traditional camera-PC-based image processing system. Figure Legend: From: Simulation platform for application development on a vision-system-on-chip with integrated signal processing J. Electron. Imaging. 2016;25(4):041004. doi:10.1117/1.JEI.25.4.041004

2 Date of download: 6/18/2016 Copyright © 2016 SPIE. All rights reserved. Simulation of conventional image sensors. Figure Legend: From: Simulation platform for application development on a vision-system-on-chip with integrated signal processing J. Electron. Imaging. 2016;25(4):041004. doi:10.1117/1.JEI.25.4.041004

3 Date of download: 6/18/2016 Copyright © 2016 SPIE. All rights reserved. Structural overview of the image sensor SoC (from Döge et al. 2 ). Figure Legend: From: Simulation platform for application development on a vision-system-on-chip with integrated signal processing J. Electron. Imaging. 2016;25(4):041004. doi:10.1117/1.JEI.25.4.041004

4 Date of download: 6/18/2016 Copyright © 2016 SPIE. All rights reserved. Depiction of the simulation system’s structure, complemented with the test environment (adapted from Reichel et al. 4 ). Figure Legend: From: Simulation platform for application development on a vision-system-on-chip with integrated signal processing J. Electron. Imaging. 2016;25(4):041004. doi:10.1117/1.JEI.25.4.041004

5 Date of download: 6/18/2016 Copyright © 2016 SPIE. All rights reserved. Depiction of the ring buffer used within the scene model. Figure Legend: From: Simulation platform for application development on a vision-system-on-chip with integrated signal processing J. Electron. Imaging. 2016;25(4):041004. doi:10.1117/1.JEI.25.4.041004

6 Date of download: 6/18/2016 Copyright © 2016 SPIE. All rights reserved. Architecture of the pixel matrix model (from Reichel et al. 4 ). Figure Legend: From: Simulation platform for application development on a vision-system-on-chip with integrated signal processing J. Electron. Imaging. 2016;25(4):041004. doi:10.1117/1.JEI.25.4.041004

7 Date of download: 6/18/2016 Copyright © 2016 SPIE. All rights reserved. Simplified equivalent circuit of a pixel (from Reichel et al. 4 ). Figure Legend: From: Simulation platform for application development on a vision-system-on-chip with integrated signal processing J. Electron. Imaging. 2016;25(4):041004. doi:10.1117/1.JEI.25.4.041004

8 Date of download: 6/18/2016 Copyright © 2016 SPIE. All rights reserved. Depiction of the interaction between development platform and simulation system. Figure Legend: From: Simulation platform for application development on a vision-system-on-chip with integrated signal processing J. Electron. Imaging. 2016;25(4):041004. doi:10.1117/1.JEI.25.4.041004

9 Date of download: 6/18/2016 Copyright © 2016 SPIE. All rights reserved. Example of the simulation system’s Python interface as well as parametrization and defect injection. (a) After loading the corresponding library, (b) the model is created and its elaboration is started. (d) To assign values to key-value pairs, (c) the interface to SensorConfig is required. (e) After the simulation is started, (f) assignments to configuration values can also occur at runtime (f). Figure Legend: From: Simulation platform for application development on a vision-system-on-chip with integrated signal processing J. Electron. Imaging. 2016;25(4):041004. doi:10.1117/1.JEI.25.4.041004

10 Date of download: 6/18/2016 Copyright © 2016 SPIE. All rights reserved. Depiction of time-dependent effects for different readout modes when observing the same scene. In (a), a global shutter readout with exposure time texpo=100 μs is depicted, while (b) shows global reset readout with initial exposure time texpo=1 μs and row time of trow=5 μs. Finally (c) is an example of rolling shutter readout with row time trow=10 μs and exposure set to 10 rows. Figure Legend: From: Simulation platform for application development on a vision-system-on-chip with integrated signal processing J. Electron. Imaging. 2016;25(4):041004. doi:10.1117/1.JEI.25.4.041004

11 Date of download: 6/18/2016 Copyright © 2016 SPIE. All rights reserved. Depiction of FPN induced by variations to the threshold voltage vth0 of the photo FET. (a) Depiction of rolling shutter readout without black value subtraction, and (b) rolling shutter readout with storage of black value after reset and subtraction during readout (simulation input image was “100130 150006 Dresden Frauenkirche winter blue sky-2” by Netopyr, published under CC BY-SA 3.0. 27 The image is licensed under CC BY-SA 3.0). Figure Legend: From: Simulation platform for application development on a vision-system-on-chip with integrated signal processing J. Electron. Imaging. 2016;25(4):041004. doi:10.1117/1.JEI.25.4.041004

12 Date of download: 6/18/2016 Copyright © 2016 SPIE. All rights reserved. Influence of defect pixels on the FAST interest point detection operator. While the green squares highlight regular FAST points inside a textured region, the red triangles show defect pixels misleadingly classified as interest points (simulation input image was “100130 150006 Dresden Frauenkirche winter blue sky-2” by Netopyr, published under CC BY-SA 3.0. 27 The image is licensed under CC BY-SA 3.0). Figure Legend: From: Simulation platform for application development on a vision-system-on-chip with integrated signal processing J. Electron. Imaging. 2016;25(4):041004. doi:10.1117/1.JEI.25.4.041004


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