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Unsharp Masking

An unsharp mask effect can be produced in the computer by applying a Gaussian blur to a duplicate of the original and then subtracting it from the original. The difference between the two images is just the detail and edges removed by the blurring. The original image is then added back to the difference to increase the visibility of the details while suppressing the overall image contrast. This interactive Java tutorial illustrates unsharp masking to increase local contrast at steps and edges. In the tutorial, the result image is automatically scaled to the range of the display so that negative values that can result from the calculation are not lost.

Interactive Java Tutorial
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The tutorial initializes with a randomly selected specimen appearing in the Specimen Image window. The Choose A Specimen pull-down menu provides a selection of specimen images, in addition to the initial randomly chosen one. The Standard Deviation slider adjusts the size of the Gaussian smoothing convolution used to create a blurred copy of the image, which is then subtracted from the original. The Amount to Add slider adjusts the percentage of the resulting difference that is added back to the original to produce the resulting Filtered Image shown on the right. For color images, the processing is applied only to the pixel brightness values, retaining the original color information.

Contributing Authors

John C. Russ - Materials Science and Engineering Dept., North Carolina State University, Raleigh, North Carolina, 27695.

Matthew Parry-Hill, and Michael W. Davidson - National High Magnetic Field Laboratory, 1800 East Paul Dirac Dr., The Florida State University, Tallahassee, Florida, 32310.


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