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Imatest Documentation Two precautions when working with figures Too many open Figures Figures can proliferate if you do a number of runs, especially SFR runs with multiple regions, and system performance suffers if too many Figures are open. You will need to manage them. Figures can be closed individually by clicking X on the upper right of the Figure or by any of the usual Windows techniques. You can close them all by clicking Close figures in the Imatest main window. Checking Close figures after save is recommended for batch runs to prevent buildup of open figures. The second figure: Noise detail (Imatest Master only) Clicking on Figures during calculations can confuse Matlab. Plots can appear on the wrong figure (usually distorted) or disappear altogether. Wait until all calculations are complete— until the Save or Imatest main window appears— before clicking on any Figures. shows the density response, noise in f-stops (a relative measurement that corresponds to the workings of the eye), noise for the third Colorchecker row, which contains primary colors, and the noise spectrum of the selected patch. The upper left plot is the density response of the colorchecker (gray squares). It includes the first and second order fits (dashed blue and green lines). The horizontal axis is Log Exposure (minus the target density), printed on the back of the ColorChecker. Stepchart provides a more detailed density response curve. The exposure error is shown in pale red if it is less than 0.25 (the maximum recommended error) and bold red otherwise. ISO Sensitivity is displayed if indicent lux has been entered. The lower left plot shows the R, G, B, and Y (luminance) RMS noise for as a function of Log Exposure each patch. RMS noise is expressed in f-stops, a relative measure that corresponds closely to the workings of the human eye. This measurement is described in detail in the Stepchart tour. It is largest in the dark areas because the pixel spacing between f-stops is smallest. The third figure: a*b* Color error The upper right plot shows noise or SNR in the third Colorchecker row, which contains the most strongly colored patches: Blue, Green, Red, Yellow, Magenta, and Cyan. Several display options are described above. In certain cameras noise may vary with the color. Problems may be apparent that aren't visible in the gray patches. The lower right plot shows the R, G, B, and Y noise spectrum of the selected patch. The 3rd patch in the bottom row (a middle gray) has beem selected. The spectrum conveys clues about signal processing, for example, an unusually rapid rolloff may indicate excessive noise reduction. The high levels or red and blue noise at low spatial frequencies is typical of Bayer sensors. The ISO speed and Exposure time from the EXIF data are displayed, if available. illustrates the color error in the device-independent CIELAB color space, where a* is the horizontal axis and b* is the vertical axis. The squares are the ideal (a*, b*) ColorChecker values, set by the ColorChecker reference setting, above. The circles are the (a*, b*) values of the actual measured ColorChecker. The numbers near the squares or circles correspond to the numbers of the ColorChecker patches: 1-6 are in the top row, 7-12 are in the second row, and 13-18 are in the third row. The numbers for patches 19-24 (the bottom row) are omitted because their (a*, b*) values cluster around (0, 0). 296 of 451
Imatest Documentation The background of the chart shows expected colors (in monitor sRGB color space) for L* around 0.9. It presents a reasonable picture of the hues associated with a* and b* (though they shift somewhat with L*). The light gray curve is the boundary of the color space (sRGB). There is significant scatter in the results because the luminance (L*) of the color patches (not displayed) varies considerably. This 2-Dimensional figure cannot display L*; a limitation is overcome in Multicharts, which has a rotatable 3D L*a*b* display. CIELAB (often shortened to LAB) was designed to be perceptually uniform, meaning that the perceived difference between colors is approximately proportional to the Euclidian distance between them, ∆E*ab (which includes luminance L*) or ∆C* (color only; omitting L*). ∆E*ab = ( (L2*-L1*) 2 + (a2*-a1*) 2 + (b2*-b1*) 2 ) 1/2 ; ∆C* = ( (a2*-a1*) 2 + (b2*-b1*) 2 ) 1/2 The smallest perceptible difference corresponds roughly to ∆E*ab = ∆C = 1. (Gaurav Sharma uses 2.3 in the Digital Color Imaging Handbook, p. 31.) CIELAB is far from perfect in this regard. ∆E*ab for the minimum perceptible color difference increases with chroma (i.e., distance from the origin, (a*i 2 + b*i 2 ) 1/2 . More accurate color difference difference formulas, ∆E*94, ∆E*CMC, and ∆E00, can be selected for display and are included in the CSV and XML output files. If you report any of the more accurate formulas, remember that they are less familiar than plain old ∆E*ab, so to avoid misunderstanding, be sure to clearly indicate which formula you are using. Mean values of ∆E*94 are about half of ∆E*ab . Mean values of ∆E*CMC are between the two. The CIEDE2000 color difference formula, ∆E00, is the emerging standard. It's the most accurate, but it's very complex and still relatively unfamiliar. It's the best choice in the long run. ∆E*94, ∆E*CMC, and ∆E00 are discussed in the Colorcheck Appendix.Several values are reported on the upper right of the figure. Mean camera chroma (%) is the average chroma of camera colors divided by the average chroma of the ideal Colorchecker colors, expressed as a percentage. The chroma of an individual color is its distance from the origin, C = (ai* 2 +bi* 2 ) 1/2 . Chroma is often referred to as saturation because more chromatic colors appear to be more saturated. The mean chroma is, Chroma = 100% mean((a*i_meas 2 + b*i_meas 2 ) 1/2 ) / mean((ai_ideal* 2 + bi_ideal* 2 ) 1/2 ) ; i_meas denotes measured values of patch i; i_ideal denotes ideal ColorChecker values ; i ≤ 1 ≤ 18 (the first three rows of the Colorchecker) ; mean(x) = Σxi / n for n = 18 values of x. Chroma is boosted when Chroma > 100%. Chroma is affected by lens quality (flare light in poor lenses decreases it) and signal processing. Many cameras and most RAW converters have adjustments for chroma (usually labelled Saturation). Chroma is not a strong indicator of image quality because it is often altered during RAW conversion and can be easily 297 of 451
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