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Measurement of image noise

Discussion in 'General Electronics' started by Sebastian, Oct 30, 2003.

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  1. Sebastian

    Sebastian Guest


    I´m working in a medical technology company and I have the following
    We are looking for a new camera for a optical device. The amount of
    light received by the device is poor, so the camera needs a high
    amplification. Unfortunately this causes image noise.
    I would like to compare different cameras and therefore I would like
    to measure the noise. Is there a simple way the determine the noise
    with a PC? I can grab a picture from the camera and do some image
    processing on it. Is it possible to measure the noise with LabView or
    the IMAQ Vision Builder from NI??? There´s no need for a precise
    measurement I just want to compare some cameras. Thanks for your help!

    Best Regards,

  2. Just calculate the SNR (signal to noise ratio) A search on google gives:,,sid7_gci213018,00.html

  3. Steve

    Steve Guest

    The difficultly here being how to quantify the signal and the noise
    power independently given the single measured signal.

    Some useful measures i've seen are:

    Peak-sig-to-noise (PSNR) => 20 * log10( 255 / variance )
    this is based on 8bit data.

    I've also seen => 20 * log10 ( ( 255 * 255 ) / variance ) used.
    variance here is the global variance of the image [ie. second
    statistical moment]

    A measure for plain SNR is: 20 * log10( mean / variance )
    again "mean" here is the global average.

    teh scaling of the log function is less important if you're doing a
    comparitive test between camera, as long as it is consistent.

    As for how well each of these compare to a more informed SNR
    calculation method, i don't know. [Anyone??]

    Good Luck
  4. AG

    AG Guest

    Grab a copy of the IGOR Pro demo

    You can use the image operations in IGOR to compute any measure you want
    for the noise level.

    The question of what would be considered a proper measure of noise is a
    whole other issue. I would recommend that you pay close attention to
    making sure that your system (sans camera) has stable/uniform
    illumination. Ideally, to compare the cameras for a given light level
    you'd have access to a uniform source (something like an integrating
    sphere or a very good diffuser). Once you acquire images of uniform
    frames at the required illumination level you can compare the signals,
    signal to noise and rms fluctuations as a function of position.


    WaveMetrics, Inc.
  5. mg

    mg Guest

    The question is, how does he separate signal from noise?

    IMAQ should have FFT routines. I would take a picture with no high spatial
    frequencies (smooth, large features). After FFT, the high frequency can
    then be attributed to noise.
  6. John Smith

    John Smith Guest

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