The Robotics Institute

Carnegie Mellon Robotics Institute

Shot noise is fundamental to photo detection. In image sensors there is an opportunity for incorporating lateral processing for reduction of both shot noise and thermal noise. Based on Bayesian argument we derive an optimal noise-smoothing model that suppresses the noise while preserving image discontinuities that are due to the scene structure. Further we show a focal plane implementation of this model using a compact electronic network.. Simulated experimental results are presented and similarities with human vision are discussed.

Keywords

Shot noise, Bayesian noise smoothing, lateral processing. resistive grids, image sensors, vision, neuromorphic circuits

Notes

Text Reference

Vladimir Brajovic, "Shot Noise Suppression in Image Sensors," SPIE, Visual Information Processing, Defense&Security Symposium, April, 2004.

BibTeX Reference

@inproceedings{Brajovic_2004_4543,
   author = "Vladimir Brajovic",
   title = "Shot Noise Suppression in Image Sensors",
   booktitle = "SPIE, Visual Information Processing, Defense&Security Symposium",
   publisher = "SPIE",
   month = "April",
   year = "2004",
}

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