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==Overview==
This method usually increases the global [[contrast (vision)|contrast]] of many images, especially when the image is represented by a narrow range of intensity values. Through this adjustment, the [[luminous intensity|intensities]] can be better distributed on the histogram utilizing the full range of intensities evenly. This allows for areas of lower local contrast to gain a higher contrast. Histogram equalization accomplishes this by effectively spreading out the highly populated intensity values which are used to degrade image contrast.Öylesine.
The method is useful in images with backgrounds and foregrounds that are both bright or both dark. In particular, the method can lead to better views of [[bone]] structure in [[x-ray]] images, and to better detail in [[photographs]] that are either over or under-exposed. A key advantage of the method is that it is a fairly straightforward technique adaptive to the input image and an [[invertible]] [[Operator (mathematics)|operator]]. So in theory, if the histogram equalization [[function (mathematics)|function]] is known, then the original histogram can be recovered. The calculation is not [[computation]]ally intensive. A disadvantage of the method is that it is indiscriminate. It may increase the contrast of background [[signal noise|noise]], while decreasing the usable [[signal]].
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