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Background Leveling

One method used to generate a background image is to remove the features from the image, leaving just the background. Of course, you can’t simply “remove” something from an image, you have to first identify the pixels that correspond to the features, and then decide what to replace those values with. One approach that has been used occasionally is to apply a Gaussian blur to the image with a large standard deviation. That is actually a poor technique for several reasons - large Gaussian filters are inefficient to apply, they mix the pixel values from the features into those of the background, rather than removing them, and the background produced is forced to vary gradually and can’t handle abrupt changes. This interactive Java tutorial illustrates the result of subtracting a background image produced by applying a filter to the original.

Interactive Java Tutorial
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The tutorial initializes with a randomly selected specimen imaged in the microscope appearing in the left-hand window entitled Specimen Image. The Choose A Specimen pull-down menu provides a selection of specimen images, in addition to the initial randomly chosen one. The radio buttons show the Original image, the background image produced by Gaussian Smoothing and the result of leveling the image contrast by removing that background, or the background image produced by a Ranking operation and the result of leveling the image contrast by removing the ranked background image.

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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