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Imatest Documentation Output noise and SNR. For example, the minimum value of the x-axis in both Figures 2 and 3 can be set between -4 and -1.5. Noise Detail (Fig. 2), Lower plot: Pixel noise or SNR Five types of display are available for the lower-left plot of the second figure. The first three are the same as the lower plot of Fig. 1. The effects of gradual illumination nonuniformities have been removed from the noise results. All displays are derived from Noise in pixels (the third selection below). In the notation below Ni is RMS noise and Si is signal (pixel) level for patch i. Noise (%) normalized to image density range = 1.5 Noise (%) normalized to 255 pixels (max of 100) Noise in pixels (maximum of 255) Pixel S/N (Signal in patch/RMS noise) dimensionless Pixel SNR (dB) (20*log10(S/N)) 100% * (Noise in pixels) divided by (the difference in pixel levels between light and dark patches that have a density difference of 1.5). This difference is close to the 1.45 White-Black difference in the ColorChecker. Useful because it references the noise to the scene: noise performance is not affected by camera contrast. 100% * (Noise in pixels) / 255 = Ni/2.55. Values 0-100. This noise measurement will be worse for higher contrast cameras. (It is affected by the gamma encoding.) Noise in pixels ( Ni ). Values 0-255. Noise in pixels ( Ni ). Values 0-255. 20 Log10(signal/noise) for each patch (where signal = pixel level). Units of dB (decibels). Doubling S/N increased dB measurement by 6.02. For this selection, SNR_BW is also displayed. SNR_BW is an average SNR based on White-Black patches (density difference = 1.5, close to the W-B difference in the ColorChecker). SNR_BW = 20 log10((SWHITE-SBLACK )/Nmid ), where Nmid is the noise in a middle gray patch (closest to nominal chart density = 0.7). The Plot box on the right allows any of the figures to be turned off or on. Incident lux (for ISO Sensitivity calculations) When a positive value of incident light level (not blank or zero) in lux is entered in this box, ISO sensitivity is calculated and displayed in the Stepchart noise detail figure. More details are on the ISO Sensitivity and Exposure Index page. The example was photographed with the Canon EOS-10D at ISO 100 and converted from RAW format using Capture One with default settings (no curves applied). The results include tonal response and noise. Colorcheck produces a similar result, but with less tonal detail. Three figures are produced for color images; two for B&W. 270 of 451
Imatest Documentation First Figure: Stepchart results The upper plot shows the average density of the grayscale patches (black curve) and first and second order density fits (dashed blue and green curves). The horizontal axis is the distance along the target. A portion of the patches themselves are shown just above the plot. The equations for the density fits are given in the Algorithm section, below. The second order fit closely matches the patches. The light cyan spikes are the differentiated and smoothed steps used to find the boundaries between zones. The lower plot shows the RMS noise for each patch: R, G, B, and Y (luminance). In this plot it is expressed as the percentage of the pixel level difference corresponding to a target density range of 1.5: the same as the white - black patches on the GretagMacbeth ColorChecker. For this camera, the pixel difference is 197.5. For this display, noise measured in pixels can be calculated by multiplying the percentage noise by 197.5. Noise can also be normalized to 255 pixels or expressed in pixels (maximum of 255). Options are described above. The high levels of Red and Blue noise in zones 3-6 may be due to imperfections in the target which are completely swamped by the noise at ISO 1600, shown below. Noise is largest in the dark areas because of gamma encoding: In the conversion from the sensor's linear output to the color space (sRGB, here) intended for viewing at gamma = 2.2, the dark areas are amplified more than the light areas and the noise is boosted as well. See Noise in photographic images for a detailed explanation of noise: its appearance and measurement. Second figure: Stepchart noise detail The second figure (Noise detail) contains some of the most important results: the tonal response curve (displayed on a log scale, similar to film response curves), noise expressed as either a fraction of an f-stop (or EV or zone), or f-stop Signal-to-Noise Ratio (SNR = S/N = 1/f-stop noise), noise or SNR (signal-to-noise ratio), based on pixel levels, expressed in one of several ways, and dynamic range (for transmission step charts). The horizontal axis for the three plots on the left is Log Exposure, which equals (minus) the nominal target density (0.05 - 1.95 for the Q-13 chart). This axis is reversed from Figure 1. The upper left plot shows the density (tonal) response (gray squares), as well as the first and second order fits (dashed blue and green lines). It resembles a traditional film density response curve. Dynamic range is grayed out because the reflective Q-13 target has too small a density range to measure a camera's total dynamic range. See Dynamic range, below. This curve is closely related to the Opto-Electronic Conversion Function (OECF), which is a linear curve of exposure vs. pixel level. The upper right box contains dynamic range results: total dynamic range and range for several quality levels, based on luminance (Y) noise. Details below. It is shown in gray when a reflective target is selected. 271 of 451
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