Brightness and contrast are the most common descriptors that people use when describing photos. One (digital) image will appear to be brighter than another if the characteristic curve is shifted upward.
Figure 2.3 shows two characteristic curves plotted on the same graph. Both have the same shape and horizontal positions, but one is higher than the other. It will appear brighter. If one of the color channels is shifted upward relative to the others, the image will have an overall color cast. So if the red curve were higher than the green and blue curves, the overall picture would have a reddish cast.
Figure 2.4 shows two characteristic curves. One has a steeper slope than the other in the central portion of the curve. That image will appear to have more contrast than the other. Dark-to-light ratios will be exaggerated. Dark areas will be darker and light areas will be lighter, with the result that differ- ences in brightness for different parts of the image will be enhanced in high- contrast versions. In the extreme, fully increasing the contrast will result in an image that has only black and white, with no intervening shades of gray. Reducing the contrast to zero will result in an image with no content— everything is a middling gray. If one of the color curves is shifted relative to
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the others, the image will have a color mismatch that varies with overall scene brightness. For example, if the green curve were to be shifted to lower contrast, the toe would be greenish and the shoulder would gain a general magenta cast.
The slope of the mid-scale or “ straight-line ” portion of the curve is referred to as gamma . When gamma equals one on a log-log plot, such as a D-Log E curve, there is a one-to-one relationship between input bright- ness and output brightness. At all other values of gamma, the relationship is nonlinear. In the 1980s the Eastman Kodak Company conducted a study of consumer preferences and found that even though the engineers preferred
FIGURE 2.3 Brightness Difference. The two graphs show a darker image and a brighter image. The shift is strictly a vertical displacement.
FIGURE 2.4 Contrast Difference. The two graphs show a response with more output per unit input—high contrast, and less output per unit input—low contrast. The shift is a slope displacement.
the logic of the gamma 1 approach, consumers preferred prints in which the gamma was a bit greater than 1. They promptly changed the gamma of their amateur negative fi lms.
In a multiple-stage process, such as fi lm photography where the camera creates a negative that is then printed onto a sheet of photographic paper with a similar characteristic curve, the gamma of the overall system is the product of the gammas of the individual parts. To make the original camera work more forgiving in the fi eld, it is common to make the camera sensor gamma relatively low. This makes it easier to get a greater dynamic range, and makes it possible for the photographer to allow for some error in setting the exposure level without ruining the photo. To compensate, the subse- quent processing of the image requires a higher gamma for the print mate- rial. This will make the overall system gamma is a bit higher than 1. For example, the gamma of a motion picture negative (camera) fi lm could equal 0.5, and the gamma of the print fi lm 2.2. The result will be an overall sys- tem gamma of 0.5 * 2.2 1.1.
The threshold point was described earlier as a level on the input axis that reliably results in a response from the sensor that is not primarily ran- dom noise. Increases in input light beyond that point result in monotoni- cally higher output responses. This point can serve as a speed point; that is, a single number that is a measure of the sensitivity of the sensor. When the level of exposure needed to get to the threshold point is, for example, 5 lux-seconds, then the speed of the sensor would be some multiple of the inverse of this number, or 0.2. The inverse is used in order to make higher numbers indicate higher sensitivity. A nice property of this convention is that when the speed point times the exposure is equal to 1.0, the sensor will be properly exposed. Most commonly, the logarithm of exposure is used instead of the absolute number since photographic systems really need to be logarithmic. The logarithm of 1.0, of course, is zero. So when considered in log space, when the speed point (in log space) plus the exposure level (in log space) is equal to zero, the camera is set for proper exposure.
Photographic speed points normally are stated according to a formula set by the International Standards Organization, and therefore are referred to as ISO values. On the log scale, equal multiples of the speed ISO will result in equal multiples in the amount of sensitivity. Accordingly, a setting of ISO 200 will be twice as sensitive as one of ISO 100. Likewise a setting of 400 will be twice as sensitive as one of 200, and four times as sensitive as one of 100. This translates into other settings as well. If a digital camera is set to ISO 400 and it gives proper exposure at 1/100 of a second, the camera could be reset to ISO 100 and 1/25 of a second and give the same level of exposure.
Figure 2.5 shows two characteristic curves that have the same shape, but one is shifted horizontally relative to the other. The sensor depicted by the curve on the left is more sensitive than the one on the right; in other words, it starts to respond reliably to light at lower levels. If the curve on the right
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responds at 34 lux-seconds (incident on the subject) and the one on the left at 17 lux-seconds, then the difference in the ISO ratings for the two sensors will be different by a factor of two as well. For example if the one on the left is ISO 200 then the one on the right is ISO 100. If a photographer were taking photos under the two conditions and the same lens opening was chosen, then the exposure times might be 1/100 of a second for the lower sensitivity sensor and 1/200 of a second for the other. The relationship between sen- sitivity and shutter opening time is what gives rise to the term speed . The higher ISO fi lm is faster than the other.
To summarize, if two characteristic curves are displaced vertically rela- tive to each other, the higher one will produce a brighter image. If one has a steeper slope than the other, it will have higher contrast. And, if two curves are displaced horizontally, the one on the left will have more sensitivity and a higher ISO.
One important point to notice. If image information falls on the sloped portion of the sensitometric curve, it can be made to show in the fi nal image. If it falls on the fl at portions of the curve, before the threshold point or after the saturation point, the information will not be recorded. With digital image processing a lot can be done to bring out weak information, but there is no way to enhance information that is not recorded in the fi rst place. Going back to the wedding picture, if the white-on-white weave in the bride’s dress is beyond the saturation point, it cannot be rendered. And, if the black velvet lapels on the groom’s tux are below the threshold level, they cannot be rendered. No amount of image processing will help. The lapels must be above the threshold level, and at the same time, the dress must be below the saturation point if both are to show in the same photo. And this must hold for all three primary color channels.
FIGURE 2.5 Speed Difference. The two graphs show two systems that vary in sensitivity or speed. The shift is strictly a horizontal displacement.
The following exercises involve using Adobe PhotoShop software tools associ- ated with some of the topics discussed in this chapter. All images not included in the text can be downloaded from the web sites.
Levels Dialog Box
Open the image Image Size.jpg. Select
Image Adjust Levels. The Levels dialog box will appear. Click the Preview checkbox. In order to use the Levels control accurately, you must understand what each control is doing to the image. All tones in an image are represented by a histogram in the Levels dialog box as shown in Figure 2.E1. A total of 256 tones are shown on a horizontal scale of 0 to 255. 0 represents a full black in the image and 255 represents a full white. The height of each bar indicates the number of pixels at that brightness level.
FIGURE 2.E1
Compare the histogram to the image in Figure 2.E2. The histogram represents the entire image. The dark areas (shadows) are represented on the left and the light areas (highlights) on the right. Notice in this image, there are many more dark pixels than there are light pixels as represented by the histogram.