Let's start way back at the basics. What makes up the pic of your dog that you just brought up on your computer screen? A very long list of numbers.
This is a small sample of the 5,161,117 numbers that make up my DSC8706 jpg It's at the boundary between the header--the zeros at the top-- and the numbers that tells a computer how bright or dark to set the three colored dots that make up the pixels on its computer screen--the hexadecimal numbers at the bottom.
At the top of the header is the EXIF data--the list of camera settings. Following that is more data about the lens I used. Finally there are pages and pages of zeros that I could fill up with metadata. If I looked up the ascii numbers for 'This is going to be tedious!!' and individually replaced some of the zeros that sentence would show up in the metadata. If I still hadn't used up all my tedium quota for the day and replaced the picture data with zeros I would eventually draw a black line across the top of DSC8706.
Once upon an ancient time that was how data editing was done. And shortly after that ancient time, when monitors that could draw pictures appeared beside humongous CPU units, programmers began writing image editors to take away the tedium of doing such mathematics on these lists of numbers.
Sometimes we only want to modify a pixel or two--covering up hot pixel noise--but usually we want to do mathematical operations on all or a good part of our image. For example, to increase the effective exposure by a stop we multiply the image numbers by 2. Or to decrease it by a stop, we multiply by 0.5. Or we multiply them by a range of numbers that depends on how far and in what direction we drag a point on a tone curve.
To sharpen an image with an unsharp mask we do "a simple linear image operation—a convolution by a kernel that is the Dirac_delta minus a Gaussian blur kernel." As per http://en.wikipedia.org/wiki/Unsharp_masking
All clear and understandable? Right? Or did you party big time the night before that early morning math class and could use a refresher explanation? Maybe you even forgot how you sharpen an image with, of all things, an unsharp mask.
Unsharp masking goes back to a time when you would stick your head under a big black cloth and take your image on a large single sheets of film. Once you developed your image of a black bird flying up in the light blue sky, you would have the B&W negative, a white bird in a black sky. If you projected this on another sheet of film, after development you would be back to a positive, a black bird against a lighter sky. If you did this as you would with a print, well focused, you would now have a 'sharp' mask.
Which wouldn't be much use. Instead. if you defocused your enlarger you would have a blurry and wider positive of your black bird, your 'unsharp' mask. When you carefully aligned the original negative and its mask and put the stack in your enlarger you have a halo around the edges of the black bird. This combination will make a print with more edge contrast than a print made with just the original negative. There isn't more detail but because of the way our eye/brain system works this print will look sharper.
Back in those film days this was another 'great in theory' procedure that hardly anyone ever used. It wasn't until our digital days when all you had to do was move a few sliders to ' convolute them sharpening kernels' that it became part of a photographer's digital development work flow.
Since a quick google of 'unsharp mask tutorial' will show why the world doesn't need another unsharp mask tutorial, I will talk about what happens when I go out my way to do it wrong.
Instead of a blackbird I start with a seagull flying over a field and pond--a peaceful and quiet country scene. (Which it ain't. The second largest mall and one of the busiest intersections in the city was behind me. A tidbit of info I'll toss in to point out that in photography framing may not be everything but it is still is a good hunk of everything.)
I ran the unsharp mask sliders up as far as RT would let me before I decided that image would be too ugly even for this do-it-wrong tutorial. So I pulled them back slightly.
Usually I see white halos when I over-sharpen, but that is because nature gave us far more darkish subjects than pure white subjects to photograph. The bird's white head has a well defined black halo while its black feet has a more traditional white halo. In the third window where there isn't much contrast between the upper part of the inner wing and the soccer field the halo is barely visible.
Traditional versions of unsharp mask have only three sliders--radius, amount and threshold. RT's version has five--Sharpen only edges and Halo control. Sharpen only edges work to prevent the sharpening of noise noise pixels. I'll go into that in another tutorial.
Activating halo control didn't completely eliminate the halos, I'd gone too far with the other settings, but it did reduce them considerable. With more normal setting, a radius of 0.8, an amount of about 150 and the default threshold of 512 I doubt I would have had to use halo control.
In the end how did I sharpening the image? By using only the contrast by details routine, a feature not found in other RAW (or jpg) converters.
What this routine does is use some fancy math to select areas that have details. The areas range from 1 or 2 pixels wide (Finest) up to about 16 to 20 pixels wide (Coarsest). Then RT multiplies those areas by whatever number you select to make them stand out in the image. Or stand out less in the image if you move the slider towards zero. With a high ISO images, one to two pixel areas are almost always noise spikes. Then I set the Finest slider down to around zero.
As with all sharpening routines it is easy to get carried away. With flower macro images setting the numbers 1 and 2 slider to slightly under 2.0 works well. With this image which has motions blur I went a bit farther in what I must confess is a rescue operation.
I was driving out of the parking
lot of my bank when I spotted the seagull. I had my camera in the back
seat but didn't have the time (or forgot) to set the camera up for bird shots. I
snapped this image at 1/500 sec instead of a motion stopping 1/1200 sec. While RT can
and has hid many of my photographic mistakes, with motion blur it can't perform
And don't be surprised if RT slows down. It's one of RT's most CPU demanding routines. With 16.2 mp images and using a less than a speed demon, four year old, 32 bit machine it add a minute or so to the RAW conversion But you will find the extra time worth it.
The top window is with sharpening, the bottom is without.
So, grab your camera and best birding lens and go off for the image that will wow the world. RT has all the power you need. The rest is up to you.