2. Gaussian sharpening
There’s plenty of resources on the web about the subject so I skip much of the basics of Photoshop USM (UnSharpMasking) and its use, why we need it, how to build masks, etc. Let me only stress again that it’s called UnSharp because it assumes the subtraction from the original picture of a blurred (unsharp) version. I’ll use a lot the “subtraction”, so here it goes a quick reminder on it, and why sharpening and blurring are close relatives inside Filter → Sharpen → Unsharp Mask...
A quick note for the reader: Grayscale images will be used throughout the article, to help us keeping the focus on tonal transitions. To mimic the effects with color pictures, use L of Lab or apply a solid white layer Color mode to have what Photoshop would consider a grayscale Luminosity version of your original. First picture (courtesy of my friend the photographer Roberto Bigano) is the starting point; then goes the blurred version and the subtraction:
(Fig. 2.1) Original picture: BW version of the painting by Paolo de Matteis “Le sante Maria, Maddalena e Dorotea” (detail) National Gallery of Cosenza, Italy (Photography © Roberto Bigano).
(Fig. 2.2) Original pictures, Blurred version and their subtraction.
Adding the subtraction to the original makes the sharpened version:
(Fig. 2.3) Original pictures plus the difference on Fig. 2.2 gives the sharpened picture.
To do this in Photoshop, I may use offset and scaling, which makes the difference channel look more familiar:
(Fig 2.4) Using a scaled version of the difference in Photoshop.
(Fig 2.5) Detail of the sharpened version using a Gaussian Blur with Radius 4.0.
A more abstract way to visualize the effect of Gaussian Sharpening, that I personally find useful for comparison purposes, is to plot the signal intensity transition (black) and its blurred version (red), their difference (green), and the original plus the difference (thicker black):
(Fig 2.6) Intensity transition and Gaussian Sharpening.
The key concept of Gaussian Sharpening is that the difference between original and blurred version is exactly what will be enhanced. If it’s used a blurring kernel (Gaussian Blur, GB, for instance) which softens edges and texture, then edges and texture will be more prominent when the difference layer will be applied to the original. Depending on the algorithm used and the processing of the blurred picture, we may end with a sharpening that affects separately different image features.
Before going any further, let me review Photoshop’s Calculations and how to use it to sharpen. Open a picture, convert to the grayscale flavor you like the most and:
- duplicate the Gray channel twice;
- call the first ORIG and the second BLUR;
- apply a GB to BLUR
- go to the menu Image, Calculation; if you want to perform a simple subtraction:
You should setup the Calculations window as follows:
(Fig 2.7) Image - Calculations window
Pay attention that the first term of the subtraction is Source #2, and the second is Source #1 (little confusing, I know). The result you have is not scaled, and for it to be applied with the appropriate blending mode (Linear Light, LL from now on) there are two slightly different ways. Let’s baptize SS1 the Subtraction with Scale = 1 which implies a later LL blend 50% opacity, and SS2 the Subtraction with Scale = 2 which implies a later LL blend 100% opacity. Both ways are useful as we’ll see soon.
(Fig 2.8) Scaling or not the subtraction (when you perform subtraction, the result is divided by the Scale factor and added to the Offset value)
Having tested a bit more the subject, I can now affirm that SS1 (LL 50%) and SS2 (LL 100%) are not exactly the same thing, so for the sake of precision, I'm suggesting you to use SS2 only. The issues in SS1 reveals in pyramid decomposition, i.e. blacks not really black (something you can easily test); nevertheless, if you're not in the middle of a decomposition (an image one, of course ;-) you can pick either SS1 or SS2.
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