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Some background: The unsharp mask is an old technique that has been used in darkrooms long before computers were capable of processing images. The original process consists of two exposures; first you create an unsharp mask by making a contact copy on low-contrast positive film, but with a distance between the original and film (and sometimes a diffusing ...


The unsharp mask will increase the perceived sharpness of an image by increasing the contrast of pixels next to each other. It does so by making darker pixels a bit darker, and brighter pixels a bit brighter. The amount parameter will control how much darker or brighter the pixels will be made. The threshold parameter will prevent the filter from having ...


Yes, from what I can gather, the settings are equivalent to those in "Photoshop" units. The radius seems to be specified the same way. For a radius less than 1 a sigma value the same as the radius is recommended. An amount of 50% is specified as 0.5. The threshold is specified as the fraction of the max color value, so 2/255 ~ 0.008. The settings that I ...


In the darkroom, one can use an unsharp mask to achieve effects similar to the digital tool of the same name. Yes, "unsharp mask" was a darkroom technique before it showed up on your computer. You start with your negative, and copy it onto another negative (forming a "mask"). The mask is dark where the original negative was clear, and clear where the ...


Bojidar Dimitrov has a great article about unsharp mask here. The article has example images and it also visualizes the parameters.


I find LR's output sharpening better than any techniques and settings I tried from PS: various unsharp mask settings (including the 2 mentioned here) sharpen > fade sharpen high pass sharpening Photokit's Output Sharpening Nothing beats my LR output sharpening with "Sharpen for Screen High" I have found out how to get them small. Update LR to 3.2, ...


The documentation of the corresponding GEGL operation can be found here. There, the meaning of the parameters is briefly explained. Standard deviation would translate to radius and scale to amount, but there may be differences in implementation of the founding operations such as the gaussian blur which may lead to different results or different parameter ...


If the images are often appearing to be over-sharpened, but you haven't noticed images being under-sharpened, then it's a good sign that you are simply sharpening them too much. Try decreasing the "amount" argument until you get more satisfactory results. For example, try halving it, then halving it again, until you notice that it's about right. I suspect,...

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