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Imatest Documentation This image has simulated uniform pixel noise (i.e., constant noise in the image file, measured in pixels). The upper plot is the tonal response (or characteristic curve) of the camera. It shows the expected ideal response for encoding with gamma = 1/2.2 = 0.4545: a straight line with slope = 0.4545 for the log-log plot. The middle plot shows noise measured in f-stops (or EV or zones). Noise increases more steeply for dark regions (large negative values of Log Exposure) in actual sensors. The lower plot shows noise measured in pixel levels, normalized to the difference in pixel levels for a density range of 1.5. It is relatively constant, showing only statistical variation, except for the brightest level (on the right), where the noise is reduced because some samples are clipped at pixel level 255. The lower plot also contains the single number used to characterize overall noise performance: the average Luminance channel noise (Y = 5.59%, on the right near the top). This number is very high; it corresponds to poor image quality. This is SNR in dB for simulated uniform pixel noise. (This display option was introduced with Imatest 2.3.16). Because of the gamma = 2.2 encoding, SNR inproves by 6.02/2.2 = 2.74 dB for each doubling of exposure (0.301 density units); roughly 9.1 dB per decade (1 density unit). Column (D): Canon EOS-10D at ISO 1600 20 of 451
Imatest Documentation Unlike the above figure (for the image in column (B)), real data for the Canon EOS-10D at ISO 1600 is used. The upper plot shows a slight tonal response "S" curve superimposed on the gamma curve (which is a straight line in this log-log plot). Some converter settings (such as "low contrast") result in a much more pronounced "S" curve. The middle plot shows f-stop noise, which increases dramatically in the dark regions. The lower plot shows the normalized pixel noise. It increases in the dark regions. This increase is due in part to the high ISO speed. Digital cameras achieve high ISO speed by amplifying the sensor output, which boosts noise, particularly in dark regions. This curve looks different for the minimum ISO speed: noise values are much lower and subject to more statistical variation. This is SNR in dB for the Canon EOS-10D at ISO 1600. (This display option was introduced with Imatest 2.3.16). SNR improves by about 6 dB for each doubling of exposure (0.301 density units); roughly 20 dB per decade (1 density unit), which is what would be expected for constant sensor noise. (This curve would be dramatically different at lower ISO speeds.) Noise summary There are two basic types of noise. Temporal. Noise which varies randomly each time an image is captured. Spatial or fixed pattern. Noise cause by sensor nonuniformities. Sensor designers have made heroic and largely successful efforts to minimize fixed pattern noise. Temporal noise can be reduced by signal averaging, which involves summing N images, then dividing by N. Picture Window Pro performs signal averaging using the Composite or Stack Images transformations, as described in Using Picture Window Pro in Astrophotography. When individual images are summed N times, the signal pixel level increases by N. But since temporal noise is uncorrelated, noise power (rather than voltage or pixel level) is summed. Since voltage is proportional to the square root of power, the noise pixel level (which is proportional to noise voltage) increases by sqrt(N). The signal-to-noise ratio (S/N or SNR) improves by N/sqrt(N) = sqrt(N). When four images are averaged, S/N is improved by a factor of 2. Several factors affect noise. 21 of 451
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