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Imatest Documentation G -0.124 0.207 -0.295 -0.037 0.922 B -0.189 0.315 -0.341 -0.037 0.907 Histograms (Imatest Master only) The histogram plot, introduced in Imatest Master 2.3.11 (July 2007), facilitates the detection and the setting of thresholds for stuck (hot, dead, etc.) pixels. Histograms of log10(occurrences+1) are displayed for the red, green, and blue channels. [The logarithm compresses the plot so even a single bad pixel is visible. log10(occurrences+1) is used because log(0) = −∞ (minus infinity), while log(1) = 0.] R, G, and B Histograms showing stuck pixels. In this example, single stuck pixels are plainly visible near levels 0 and 252. Altough these stuck pixels were synthesized, their levels is slightly different due to JPEG compression (they were the same in a TIFF file). The dead pixel threshold is shown on the left in blue; the hot pixel threshold is shown on the right in red. You can quickly see if the thresholds are set correctly— if they are outside the valid density region and if the dead and hot pixels are above and below their respective thresholds. You can change threshold settings and rerun Light Falloff if necessary. Noise detail (Imatest Master only) shows an exaggerated or pseudocolor image of the noise detail with long-range density variations removed. Four options are available: Exaggerated local noise (standard) Exaggerated image of local noise Local noise with added contours Exaggerated image of local noise with added contours Pseudocolor contours with colorbar Spot detection w / threshold (pseudocolor) 3D Pseudocolor Contours shaded Pseudocolor image of local density variations. The image has been smoothed. Colors vary from image to image: the color map covers the density range of the image. Pseudocolor image emphasizing spots. Fixed color map. Image is normalized to the mean density. For clarity, only densities between 0.9 and 1 are displayed in the color map. 3D pseudocolor image may be rotated for enhanced visualization. Shading emphasizes contour shapes. 3D Pseudocolor Contours The Colormap (which relates color to levels) is more accurate without shading. 3D Inverted Pseudocolor Contours shaded 3D Inverted Pseudocolor Contours 3D Spot detection, pseudocolor shaded 3D Spot detection, pseudocolor Inverts the data (Z-axis) 3D spot detection. The Z-axis is always inverted so spots stand out. 340 of 451
Imatest Documentation The local noise figures are produced by 1. 2. Subtracting a highly smoothed version of the image from the image itself. This removes broad image variations (low spatial frequencies), leaving only the fine detail. (The signal is highpass filtered.) Exaggerating the fine detail by a factor 5x or 10x, depending on the signal-to-noise ratio (the average pixel level of the original image divided by the standard deviation of the difference image (the results of step 1), i.e., the RMS noise). Adding an offset to the the exaggerated signal so the average level of the image is displayed as middle gray. If Local noise with added contours is selected, contours are calculated by subtracting the same highly smoothed version of the image from a moderately smoothed version of the image. Smoothing is necessarily because noise would make the contours unintelligibly rough. The first image (below) shows noise detail for the Canon EOS-20D at ISO 1600 with the 10-22mm lens set to f/4.5. No surprises here; electronic noise dominates. Noise detail for Canon EOS-20D, ISO 1600, 10-22mm lens, f/4.5. The second image (below) shows noise detail for the Canon EOS-20D at ISO 100 with the 10-22mm lens set to f/8. Thanks to the small aperture, some very faint dust spots are visible. The dust is on the anti-aliasing/infrared filter/microlens assembly in front of the sensor. This assembly can be well over 1 millimeter thick. Stopping the lens down (increasing the f-stop setting) reduces the size of dust spots but makes them darker. This image has a surprise in the form of concentric circles: bands where the noise appears to be higher or lower than the remainder of the image. This may be caused by (a) the Analog-to-Digital (A-D) converter in the image sensor chip, which can have small discontinuities when, for example going from level 127 to 128: binary 01111111 to 10000000, or (b) JPEG artifacts. Rrecall that these noniniformities are exaggerated by a factor of 10: they would be invisible or barely visible on an actual image; you might seem then faintly in smooth areas like skies. 341 of 451
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