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Real World Camera Raw with Adobe Photoshop CS4: Evaluating Images

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Bruce Fraser and Jeff Schewe explain the three features that Camera Raw offers that help you evaluate the raw image: the histogram, the image preview, and the RGB readout and color samplers.
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Before starting to edit a raw image, it’s always a good idea to do a quick evaluation. Is the image overexposed or underexposed? Does the subject matter fall within the camera’s dynamic range, or do you have to sacrifice highlights or shadows? Camera Raw offers three features that help you evaluate the raw image and answer these questions:

  • The histogram lets you judge overall exposure and detect any clipping to black, white, or a fully saturated primary.
  • The image preview shows you exactly how the converted image will appear in Photoshop, and the clipping display, available when you adjust the Exposure and Shadows sliders, lets you see exactly which pixels, if any, are being clipped.
  • The RGB readout and color samplers let you sample the RGB values from specific spots in the image.

If an image is too dark or too light, you need to decide whether to fix it by adjusting Exposure or Brightness. If it’s too flat, you need to decide whether to increase the Contrast or add snap to the shadows with the Blacks control. Camera Raw’s histogram helps you make these decisions by showing at a glance what’s happening at the extreme ends of the tone scale.

The histogram

Camera Raw’s histogram is simply a bar chart that shows the relative populations of pixels at different levels. The colors in the histogram show what’s going on in each channel.

Spikes at either end of the histogram indicate clipping—white pixels mean that all three channels are being clipped, and colored pixels indicate clipping in one or two channels (see Figure 5-4).

The histogram can help you determine whether the captured scene fits within the camera’s dynamic range. If there’s no clipping at either the highlight or the shadow end, it clearly does. If there’s clipping at both ends, it probably doesn’t. If there’s clipping at only one end, you may be able to rescue highlight or shadow detail (if you want to) by adjusting the Exposure slider.

The histogram also shows clipping in individual channels. Typically, clipping in one or two channels indicates one of two conditions:

  • The RGB space selected in the Space menu is too small to hold the captured color. In that case, try switching to a larger space if the color is important.
  • You’ve pushed the saturation so far that you’ve driven one or more channels into clipping. Again, this isn’t necessarily a problem. To see exactly what’s being clipped, you can use the Exposure or Shadows slider’s clipping display, which we’ll discuss next.

Image preview

The main function of the image preview is, of course, to show you how the converted image will appear. But it also offers a couple of indispensable tricks in the form of the highlight clipping display and shadow clipping display, which you access by using the Option key in conjunction with the Exposure and Shadows sliders, respectively. Hold down the Option key, and then hold down the mouse button on either slider to see the clipping display. The display updates dynamically as you move the slider, so it’s useful for editing as well as evaluation.

  • Exposure clipping display. Holding down the Option key as you move the Exposure slider turns the image preview into a highlight clipping display—see Figure 5-6.

    Unclipped pixels display as black. The other colors show you which channels are being clipped to level 255. Red pixels indicate red channel clipping, green pixels indicate green channel clipping, and blue pixels indicate blue channel clipping. Yellow pixels indicate clipping in both red and green channels, magenta pixels indicate clipping in the red and blue channels, and cyan pixels indicate clipping in the green and blue channels. White pixels indicate that all three channels are clipped.

    Of all the controls in the Basic panel, the Exposure slider is the most critical due to the nature of linear captures, which devote many more bits to describing the highlights than to describing the shadows. On the vast majority of images, the first edit is to set the Exposure slider so that the highlights are as close as possible to clipping. If the image exceeds the camera’s dynamic range, you may choose to sacrifice highlight detail when the nature of the image dictates that the shadow detail is more important. But even then, careful setting of the Exposure slider is vital, and the clipping display is invaluable in making that setting. However, even with highlight clipping, the use of Recovery can tame all but the most blown-out of highlight detail. Recovery combined with careful use of point curves can tease out highlight detail where none may be obvious.

  • Shadows clipping display. Holding down the Option key as you move the Shadows slider turns the image preview into a shadow clipping display—see Figure 5-7.

Unclipped pixels display as white. The other colors show you which channels are being clipped to level 0. Cyan pixels indicate red channel clipping, magenta pixels indicate green channel clipping, and yellow pixels indicate blue channel clipping. Red pixels indicate clipping in both green and blue channels, green pixels indicate clipping in the red and blue channels, and blue pixels indicate clipping in the red and green channels. Black pixels indicate that all three channels are clipped.

While the histogram shows you whether or not clipping is taking place, the clipping displays show you which pixels are being clipped. If you want to evaluate clipping on single pixels, you’ll need to zoom in to 100% view. Camera Raw does its best to show you clipping at lower zoom percentages, but it’s only completely accurate at 100% or higher zoom levels.

RGB readout

The RGB readout (see Figure 5-8) lets you sample the RGB values of the pixel under the cursor. At 100% or lower zoom percentages, the readout always reports the average of a 5×5 sample of screen pixels. At higher zoom levels, the readout is an average of 5×5 actual image pixels, which is the minimum sample size.

The RGB readout helps you distinguish between, for example, a yellow cast and a green one, or a magenta cast and a red one. Sample an area that should be close to neutral. If the blue value is lower than red and green, it’s a yellow cast; if the green value is higher than red and blue, it’s a green cast. See Figure 5-8 for examples.

If you need to keep track of important colors in the image, you can use the Color Sampler tool (see Figure 5-9) to place up to nine color samplers. So, including the RGB cursor readout, you can track ten sets of color values.

The evaluation process

The first thing you should do in your evaluation is simply look at the image. We generally suggest setting your Camera Raw defaults without Apply Auto Tone Adjustments selected. You need to be able to see the effects of bracketing rather than having Camera Raw normalize all your exposures. Besides, you can always click the Auto button in the Basic panel to see what Camera Raw might do. At default settings, images usually look flat and are often too bright or too dark.

  • The first thing we do is check for clipping. An image that’s too dark may be underexposed, requiring an Exposure adjustment, or it may be holding some bright highlights and need a Brightness adjustment to remap the midtones instead. By the same token, an image that’s too bright may be overexposed, requiring highlight recovery with the Recovery slider, or it may need darkening of the midtones by reducing the Brightness value. The histogram and clipping displays help determine which is the case.
  • It’s much easier to add contrast than to reduce it. Depending on the tonal range involved, it may be best to use the Blacks slider, the Contrast slider, the Curve panel, or any combination thereof, but only do so after you’ve set the endpoints.
  • If you need to make big Exposure moves, do so before setting white balance, because changes in the Exposure value can have a big effect on the white balance. Other than that, it doesn’t really matter when you set the white balance.
  • After evaluating the tone, evaluate the color starting with white balance. While you might presume that known neutrals should be neutral, that’s not always the case. It all depends on the color of light in which you shot. A neutral color shot at sunset should be warm in color, not dead neutral. Once a shot is white balanced, you can look at overall saturation or the rendering of certain colors.
  • After editing for tone and color, zoom in to 100% or higher, and check for image sharpness, color and luminance noise, and for chromatic aberration and fringing. For maximum image quality, you must correct for chromatic aberration.

The evaluation process has been forever changed with Camera Raw 5’s ability to do local tone and color corrections. You no longer need to go to Photoshop just to adjust a local area in your image. However, the local adjustments come at a price—the tools in Camera Raw are not as flexible as those found in Photoshop and adding lots and lots of local adjustments will slow down the processing of raw files, sometimes by a lot. So, use good judgment when deciding when and where to make these corrections. But it’s way cool that you can do nondestructive brush and graduated adjustments in Camera Raw!

The histogram is plotted based on the Workflow settings and the color space you’ve chosen. The display is based on 8-bit/channel accuracy in the gamma of your color space. To view a 16-bit/channel histogram would be less useful, since the size would constrain how accurate it could be plotted. The same could be said for viewing a linear gamma histogram. Thus, the final color space and its gamma is the optimal choice for the histogram display.

We’d like to stress that there is no such thing as a “perfect histogram.” Nor should you try to adjust an image to arrive at some sort of optimal shape. A histogram whose concentration of data is in the shadows with little or no data in the highlights may indicate underexposure, whereas concentration in the highlights may indicate overexposure. These sorts of shapes can give you hints as to what adjustments you’ll need to make to more evenly distribute the levels in your image.

The RGB readout (see Figure 4-7) shows the RGB values that will result from the conversion at the current settings; the readout displays the RGB value for the pixel under the cursor. It always reads 5-by-5 screen pixels at zoom levels of 100% or less, so it may give different values at different zoom levels. When you fit the entire image into Camera Raw’s preview, you’re sampling an average of a fairly large number of pixels—the exact number depends on the camera’s native resolution and the size you’ve chosen from the Size menu in the Workflow controls. At zoom levels greater than 100%, the sample size is always 5×5 actual image pixels.

The EXIF readouts (also shown in Figure 4-7) transcribe the embedded EXIF metadata to provide readings familiar to photographers. The accuracy of the readouts will depend entirely on the way in which cameras store the EXIF metadata. Sometimes that can be ambiguous, particularly when reading lens data. Not all camera makers provide data on all lenses, and some third-party lenses can cause either inaccurate or faulty lens information.

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