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Adaptive histogram equalization (AHE) is a computer image processing technique used to improve contrast in images. It differs from ordinary histogram equalization in the respect that the adaptive method computes several histograms, each corresponding to a distinct section of the image, and uses them to redistribute the lightness values of the image.
For example, if applied to 8-bit image displayed with 8-bit gray-scale palette it will further reduce color depth (number of unique shades of gray) of the image. Histogram equalization will work the best when applied to images with much higher color depth than palette size, like continuous data or 16-bit gray-scale images.
Contrast resolution or contrast-detail is an approach to describing the image quality in terms of both the image contrast and resolution. Contrast resolution is usually measured by generating a pattern from a test object that depicts how image contrast changes as the structures being imaged get smaller and closer together.
The optical transfer function (OTF) of an optical system such as a camera, microscope, human eye, or projector is a scale-dependent description of their imaging contrast. Its magnitude is the image contrast of the harmonic intensity pattern, + (), as a function of the spatial frequency, , while its complex argument indicates a phase shift ...
Graphics card and monitor contrast and brightness have an influence on effective gamma, and should not be changed after gamma correction is completed. The top two bars of the test image help to set correct contrast and brightness values. There are eight three-digit numbers in each bar.
Images can often be improved – or even transformed – by using graphics software such as Photoshop or the free GIMP and Paint.NET applications. Many other programs also have photo-enhancing tools, including facilities for semi-automatic image enhancement, so that you need only click a button, or choose a thumbnail, to have a positive effect on image quality.
The contrast enhancement tries to change the intensity of the pixel in the image, particularly in the input image for the purpose to obtain a more enhanced image .It is based on the number of techniques namely local, global, dark and bright levels of contrast .The contrast enhancement is considered as the amount of color or gray differentiation ...
Edge enhancement is an image processing filter that enhances the edge contrast of an image or video in an attempt to improve its acutance (apparent sharpness).. The filter works by identifying sharp edge boundaries in the image, such as the edge between a subject and a background of a contrasting color, and increasing the image contrast in the area immediately around the edge.