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Rank Masking

One of the characteristics of the unsharp mask is the formation of bright and dark “haloes” adjacent to the dark and bright borders (respectively) of structure in the image. This increases their visibility, but can hide other nearby information. A related approach using neighborhood ranking rather than Gaussian blurring alleviates this problem. The method applies a median filter to remove fine detail, subtracts this from the original to isolate the detail, and then adds the original image back to enhance the visibility. This method is called a rank mask, but is sometimes (incorrectly) referred to as a top hat filter. This interactive Java tutorial illustrates rank masking to increase contrast of fine details.

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 Neighborhood Radius slider adjusts the size of the neighborhood around each pixel in which a median filter is applied, 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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