Image Enhancement

Authored by: S. Palanikumar

Encyclopedia of Image Processing

Print publication date:  November  2018
Online publication date:  November  2018

Print ISBN: 9781482244908
eBook ISBN: 9781351032742
Adobe ISBN:

10.1201/9781351032742-140000133

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Abstract

Image enhancement is the process by which an input image is preprocessed to fit for the application. Enhancement includes improving contrast, brightness, and edge or reducing the noise of the image. The principal objective of enhancement is to process an image so that the result is more suitable than the original image for a specific application. Consequently, the enhancement methods are application specific and are often developed empirically. Image enhancement can be done in either spatial domain or frequency domain. Contrast stretching, image negative, gray-level slicing, bit-plane slicing, compression of dynamic range, histogram equalization, and histogram specification are some of the spatial domain techniques. Spatial domain techniques modify the gray-level value using the transformation function. Low-pass filter, high-pass filter, and band-pass filter are some of the frequency domain techniques. First, frequency domain methods transform the image from spatial domain to frequency domain using the transformation function, and then the modification is done in the frequency domain itself. Finally, the image is brought to spatial domain using inverse transformation function. Spatial domain processing methods include point, mask, and global operations, but frequency domain operations, by nature of the frequency transforms, are global operations. Of course, frequency domain operations can become mask operations, based only on a local neighborhood, by performing the transform on small blocks instead of the entire image. Image enhancement has played and will continue to play an important role in different fields such as medical, industrial, military, and scientific applications.

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