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Empirical Characterization of Camera Noise

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNIP,volume 7914)

Abstract

Noise characterization is important for several image processing operations such as denoising, thresholding, and HDR. This contribution describes a simple procedure to estimate the noise at an image for a particular camera as a function of exposure parameters (shutter time, gain) and of the irradiance at the pixel. Results are presented for a Pointgrey Firefly camera and are compared with a standard theoretical model of noise variance. Although the general characteristic of the noise reflects what predicted by the theoretical model, a number of discrepancies are found that deserve further investigation.

Keywords

  • Noise Variance
  • Exposure Parameter
  • Gamma Correction
  • Exposure Setting
  • CMOS Image Sensor

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© 2013 Springer-Verlag Berlin Heidelberg

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Baumgartner, J., Hinsche, M., Manduchi, R. (2013). Empirical Characterization of Camera Noise. In: Carrasco-Ochoa, J.A., Martínez-Trinidad, J.F., Rodríguez, J.S., di Baja, G.S. (eds) Pattern Recognition. MCPR 2013. Lecture Notes in Computer Science, vol 7914. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38989-4_1

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  • DOI: https://doi.org/10.1007/978-3-642-38989-4_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38988-7

  • Online ISBN: 978-3-642-38989-4

  • eBook Packages: Computer ScienceComputer Science (R0)