Cleaning up scanned halftones

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Photoshop offers one additional filter in the Filter ^ Noise submenu called Dust & Scratches. The purpose of this filter is to remove dust particles, hairs, scratches, and other imperfections that may accompany a scan. The filter offers two options, Radius and Threshold. As long as the offending imperfection is smaller or thinner than the Radius value and different enough from its neighbors to satisfy the Threshold value, the filter deletes the spot or line and interpolates between the pixels around the perimeter.

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Figure 10-45: Here you can see the difference between sharpening a digital photograph right off the bat (top) and waiting to sharpen until after you've prepared the image with Median, Gaussian Blur, and Unsharp Mask (bottom).

But like so many automated tools, this one works only when conditions are favorable. I'm not saying that you shouldn't ever use it — in fact, you may always want to give this filter the first crack at a dusty image. But if it doesn't work (as it probably won't), don't get your nose out ofjoint. Just hunker down and eliminate the imperfections manually using the rubber stamp tool, as explained in the "Touching up blemishes" section of Chapter 7.

Now, as I say, Dust & Scratches was designed to get rid of gunk on a dirty scanner. But another problem that the filter may be able to eliminate is moire patterns. These patterns appear when scanning halftoned images from books and magazines. See, any time you scan a printed image, you're actually scanning a collection of halftone dots rather than a continuous-tone photograph. In most cases, the halftone pattern clashes with the resolution of the scanned image to produce rhythmic and distracting moires.

Caution When scanning published photographs or artwork, take a moment to find out if what you're doing is legal. It's up to you to make sure that the image you scan is no longer protected by copyright — most, but not all, works over 75 years old are considered free game — or that your noncommercial application of the image falls under the fair-use umbrella of commentary or criticism.

The Dust & Scratches filter can be pretty useful for eliminating moires, particularly if you reduce the Threshold value below 40. But this also goes a long way toward eliminating the actual image detail, as shown in Color Plate 10-7. This figure features an image scanned from a previous issue of Macworld magazine. (Because I created the original image, Macworld probably won't sue me, but you shouldn't try it.)

The left half of Color Plate 10-7 shows the individual color channels in the image; the right half shows the full-color image. I've blown up a detail in each image so that you can better see the pixels in the moire pattern.

The top example in the color plate shows the original scanned image with its awful moires. (Actually, I've slightly exaggerated the moires to account for any printing anomalies; but believe me, with or without enhancement, the image is a mess on screen.) The middle example shows the same image subject to the Dust & Scratches filter with a Radius of 2 and a Threshold value of 20. The moires are gone, but the edges have all but disappeared as well. I'm tempted to describe this artwork using adjectives such as "soft" and "doughy," and them are fightin' words in the world of image editing.

But what about that bottom example? How did I manage to eliminate the moires and preserve the detail that is shown here? Why, by applying the Gaussian Blur, Median, and Unsharp Mask filters to individual color channels.

The first step is to examine the channels independently (by pressing Ctrl+1, Ctrl+2, and Ctrl+3). You'll likely find that each one is affected by the moire pattern to a different extent. In the case of this scan, all three channels need work, but the blue channel — the usual culprit — is the worst. The trick, therefore, is to eliminate the patterns in the blue channel and draw detail from the red and green channels.

To fix the blue channel, I applied both the Gaussian Blur and Median commands in fairly hefty doses. I chose Filter ^ Blur ^ Gaussian Blur and specified a Radius value of 1.5 pixels, rather high considering that the image measures only about 300 pixels tall. Then I chose Filter ^ Noise ^ Median and specified a Radius of 2.

The result was a thickly modeled image with no moires but little detail. To firm things up a bit, I chose Filter ^ Sharpen ^ Unsharp Mask and entered 200 percent for the Amount option and 1.5 for the Radius. I opted for this Radius value because it matches the Radius that I used to blur the image. When correcting moires, a Threshold value of 0 is almost always the best choice. A higher Threshold value not only prevents the sharpening of moire pattern edges but also ignores real edges, which are already fragile enough as it is.

The green and red channels required incrementally less attention. After switching to the green channel, I applied the Gaussian Blur filter with a Radius of 1.0. Then I sharpened the image with the Unsharp Mask filter set to 200 percent and a Radius value of 0.5. In the red channel (Ctrl+1), I applied Gaussian Blur with a Radius value of 0.5. The gradual effect wasn't enough to warrant sharpening.

When you're finished, switch back to the RGB view (Ctrl+0) to see the combined result of your labors. (Or keep an RGB view of the image up on screen by choosing Window ^ New Window.) The focus of the image will undoubtedly be softer than it was when you started. You can cure this to a limited extent by applying very discreet passes of the Unsharp Mask filter, say, with an Amount value of 100 percent and a low Radius value. Keep in mind that oversharpening may bring the patterns back to life or even uncover new ones.

Tip One last tip: Always scan halftoned images at the highest resolution available to your scanner. Then resample the scan down to the desired resolution using * Image Image Size, as covered in Chapter 3. This step by itself goes a long way toward eliminating moires.

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