Image Toolbox for CMOS Image Sensors Fast Simulation

David Navarro; Ian OConnor

Image Toolbox for CMOS Image Sensors Fast Simulation

David Navarro * §

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Ian OConnor

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Image Toolbox for CMOS Image Sensors Fast Simulation

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CST2V449

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Abstract

This paper presents a new toolbox, dedicated to image sensors designers. It permits fast analog simulations with a novel parametric simulation method. Image sensor matrixes are composed of millions of pixels. Such architectures are long to simulate, if not impossible; and input/ output data management is complex. A graphical toolbox has been developed in Cadence Analog Design Environment (ADE) to overcome these problems. That toolbox has been completely written in Cadence SKILL language. It permits to manipulate images as input, launch parametric analysis on a single pixel, and interpolate results for all pixels in the matrix. It then automatically generates images at output, in order to check the quality of microelectronic design. Low level aspects can also be analyzed at system (image) level.

References

8 Cites in Article

Reference Format

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

David Navarro, Ian OConnor. 1970. "Image Toolbox for CMOS Image Sensors Fast Simulation". Global Journal of Computer Science and Technology - F: Graphics & Vision GJCST-F Volume 13 (GJCST Volume 13 Issue F3).

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GJCST Volume 13 Issue F3

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

APS image sensor microelectronic design Modeling Simulation

Classification

GJCST-F Classification I.4.8

Submission ReceivedDecember 14, 2012
Peer Review Double Blind
Handling Editor
Accepted January 5, 2013
Published January 15, 2013

Version of record

v1.2

Language

English

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Article Matrices

Total Score: 173

Country: France

Subject: Global Journal of Computer Science and Technology

Authors: David Navarro, Zhenfu Feng, Ian OConnor (PhD/Dr. count: 0)

View Count (all-time): 440

Total Views (Real + Logic): 6071

Total Downloads (simulated): 374

Publish Date: 2013 01, Tue

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Total Views: 6.1K

Total Downloads: 374

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