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Review the scanning techniques graphics professionals and photographers use, while delving into workflow considerations and the advanced image-quality controls available in most scanning software. Author Taz Tally explains the core concepts, such as how resolution and interpolation affect scans; introduces the industry-standard SilverFast scanning software; and shares the settings to achieve the best results from a scan. The course also covers keeping your scanner and its parts clean and free of dust, and includes a variety of start-to-finish scanning tasks.
Let's investigate scanning images that are distressed or damaged and maybe even in a need of a lot of photo restoration. In fact, the image that we're going to use here that you see in the Preview screen is an image that Janine Smith sent to me, and Janine Smith teaches a class at Lynda.com called Photo Restoration with Photoshop. And this is one of the images that she works with in her class. So we're kind of combining efforts here. She sent me this image do a high- quality scan and then, I'm going to send it back to her and she is going to use it into her Photo Restoration class.
So when you get done with the scanning course, be sure to go check out Janine Smith's Photo Restoration with Photoshop course to see how far you can take this image with a good quality scan. So we better do a good job here, Janine will not be happy. I'm actually going to do two scans. One scan is I'm going to do is good a job as we kind of get ready to just take it, scan it, and go to print. And then we're going to evaluate that image in Photoshop a little bit and maybe see what we can do to fine-tune that to make it even a little bit better for photo restoration. So let's evaluate this image and see what we've got.
Obviously, very, very low contrast, the image is very faded, like it has a color cast as we saw because almost all faded images have color cast to them. And you can really see this on color images that tend to get very green and blue as they age a lot of times. Others get very, very red. This one has got a real red color cast to it. It's hard to tell how this one actually started out. It might have actually started out as a single ink or as a sepia image, it's hard to tell. And of course, this poor gal is turned right now through her head, but Janine will fix that.
We can do similar types of analysis with this image that we do without this. We can go check out what the highlight and shadow values are, so let's go do that and see what we get. There's the highlight, of course, we gave it to us on the tare. All right, And then shadow, so we get a shadow value here on the dress. Sometimes on images like this when you go to look for the shadow value, if it's got type on it like this, it'll actually choose the type. If it does that, you can do this, set your highlights and shadows and the pull this back down if you want that to be part of the scan.
So you can always eliminate some portion of the image before you set highlights and shadows if you're getting a highlight and a shadow in the area that you don't want it. Now I could do that here, for instance, where I can get rid of all of these, if I wanted to see well, what's the lightest portion of this image, outside of that area right there so I could pull that or maybe what we'll do is pull this in here, there we go and then do a highlight check. When we see that highlight goes right down there. And then we'll do the shadow up right there, here we go.
We're not concerned so much about that value right there. And if we set that, we can always use it later, but we're going to do put our number one value down here in this portion of the image which is part of the paper that surrounds it but it's not part of the tear. All right, So is there any other portion of this image that's important, well, I would probably put one right on this gal's face, maybe on the light portion of her face just to make sure, we've got grayscale values there. When all is said and done, there we go. So there's our highlight, there's our shadow, and we've got one in the tear.
It'd be nice if we had some data to work with there, but we'll see. And then we have the type at the bottom. Where do we go from here? Well, let's go over to our Histogram tool. You can really see the color cast in here because of the offset of the red in relationship to the green and the blue. This is a very yellow image and of course you combine red and green together to make yellow and these are offset way to the right of the blue. So the histograms agree with our visual evaluation of having a strong red, green or yellow color cast. The first adjustment we're going to make here and understand there is really no highlight in this image.
It's just kind of the lightest portion of the image which is down that's not really a highlight in the image. This is a shadow portion of the image but it looks to me like it's really kind of the damaged portion of the image which is likely going to be taken away. So that's not super-helpful to us, is it? We might move that in just a minute. What we do have is histograms and very often with images where we don't really have highlights and shadows or we don't have neutrals, boy, the histograms come in super-handy to help us evaluate and then adjust images. Well, since these are so offset, we're not going to just do a master histogram.
That doesn't help us very much because it keeps the color cast. We're going to go into the individual channels. And on our first correction, remember I told you we're going to do two. In the first one, I'm going to take this highlight, I'm going to pull it all the way in. A lot of times these flat areas here is noise in the image, you're not quite sure where the data starts and where it doesn't, but I'm going to bring this in right to the start of where the significant data is in this image where it boom, jumps up. Remember, this first one is scan and take it to print, not intending to do much in Photoshop. And then I'm going to take the shadow and again, move it in and particularly where you've got the broken data that's very often noise, but I'm going to going to bring it into where the significant data jumps up under the red.
I'm going to do the same thing on all three channels. Red, Green, and then Blue. What this basically does is it lines up all the highlights and shadow points in the three images. And notice it takes out a lot of that color cast of that image just by doing that. I'm putting all the way up to the beginning, and then I'm going to click OK. Huge improvement in this image already! Notice that we have our number two point over there and we look at in some detail.
It does look like a damaged point, so we might move it over here, maybe in the shadow portion of the dress to see where we are. There is our highlight which is down there in the fold. Point number four is probably one of the most important points we've got here. 242, 241, 235. That's a very light portion of the image that we want to look at. We want to make sure there's plenty of data there to print and to work with. So we wouldn't want this to go any higher than this 242, 241 because that's about 5% white highlight. If we're any lighter than that, well, we probably want to go back and make a fine-tune adjustment with our histogram.
Could we improve this image a little bit more? Well, we could come in here into our curves and we could lighten the overall image and we could improve contrast. That might do a little bit of a contrast improvement. Little bit goes on right there. Am I going to sharpen this image? Probably not. In fact, the images that have this much damage and repair, sharpening them just brings out the damaged areas more than anything else. So I'm not going to apply any sharpening to this. I might do some descreening if there were any patterns in here.
I'm not exactly sure what Janine is going to do as far as repairing this image. So I'm going to leave this the way it is. But remember, this one actually is going to go to print. So I'm not going to anything else. I'm just going to do a basic tonal adjustment in this image and we're going to go to scan. And let's see, we've got a 2 inch x 3 inch image and we'll do 300 pixels per inch. I do a full scan and with an image like this we're just going to go to print, we'll do 48 -> 24 Bit Color. So I'm going to click Scan and we're going to call this one Torn Woman_RGB, take out the 16, all right, we're going to 24 bit, and then click Save.
So vastly improved, still need lots of work in terms of retouching. But what I want to do now is I want to bring up the Layers panel and I want to add a curves adjustment layer. Coming up, tick over the image just a little bit, but most importantly what I want to do is take a look at the histogram. The other thing that you can view in Photoshop is just go into and choose Histogram. Both of these are useful. This one useful for kind of tweaking, and this one for just looking at the data in the image.
Notice that we've got a little spike here in the highlight, little spike in the shadow. What that means is we've pulled the highlights and shadow values and just a little bit too far by looking at the histogram. This is why the Histogram is such a valuable tool, because rather than kind of measuring these values all over the image, we can look at the Histogram and see the distribution of data across the entire image. If we print this image like this, it's a dramatic improvement from what we had. No doubt about it. The image that I want to send to Janine, I want it to be as good as it can possibly be. So I'm going to back in and I'm going to back off in those Highlights and Shadows just a little bit on these three channels.
But notice how these three channels now line up, all right, because we did a Histogram adjustment on the individual channels, took out the horrible color cast. So let's go back and redo the scan just a little bit different this time. And in fact, what I want to deliver is a 48 bit color image. So I'm going to give Janine lots of grayscale values to work with. We won't see much impact on screen here, but we are going to give Janine far more grayscale values to work with. Then let's go back into our histogram here and I'm just going to back this off, our histogram, just a little bit in the highlights and shadows, just a tad.
We said we're not quite sure what's data and what's noise in here, and red and green, same thing, just back off a little bit. I want to do as much tone compression as I can get away with, so I'm stuffing lots of grayscale values where the image data actually is. I don't need a lot of grayscale values out here in the flats. But I don't want to do too much tone compression. So I'm going to click OK, and in fact, I'm going to come in here and I'm just going to take out all the Contrast Correction because I'm going to leave that for the final analysis after Janine finishes her editing. There we go! We're going to save this out as a 48 bit image, so we're going to call this RGB and then Hyphen, either 48 or 16 bit per channel or total 48 if you want.
And that tells you that you've scanned this as 48 bit, so that you know that it's ready for editing and I'm going to click Save here. There we go! And let's look at this image now, this is the 48 bit one. And when we look at the histogram, there's still just a little bit of tick up, little bit less. So one more and after you get used to this, after a while you get real good at choosing in how much you want to back off, so we just go a little bit more. And we're doing it progressively so you can see the difference and with just a little bit of adjustment and a little bit more.
Okay, and then scan. There we go! That's just about right. It's just a tiny little tick up here and a tiny little one in the Shadow, but you can see what happens as we move those highlights and shadows out a little bit more and little bit more. So I'll probably perform the scan one more time and take out those ticks completely, but you get the idea about how to get as much tonal data as you can in your image without the tick ups on the end.
And then we're going to send this to Janine and she is going to use it in her course and she is going to make it look really good. So there's scanning distressed images.
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