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Histogram Equalization

This interactive Java tutorial illustrates the effects of histogram equalization using the cumulative histogram of an image. If the cumulative histogram, which varies from 0 to 100 percent, is used as the transfer function it produces an image that has brightness values spread out to cover the entire range available. As shown in the tutorial, the new cumulative histogram becomes a straight line, and peaks in the histogram are spread out so that small differences become visible. Comparison of images acquired with varying conditions, including changing specimen density, may be facilitated.

Interactive Java Tutorial
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The tutorial initializes with a randomly selected specimen imaged in the microscope 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 histogram of the image brightness values is shown on the right both as the conventional plot of the number of pixels as a function of brightness, and as the cumulative plot. Clicking on the Grayscale Image button shows just the monochrome image and values, while clicking on the Color Image button shows the image in color and the histogram of the weighted luminance values. The buttons at the right display either the Original image and histogram or the Equalized image and histogram in which peaks are spread out and valleys contracted in the conventional histogram to produce a linear cumulative histogram.

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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