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The basic intent of the contrast enhancement technique is to adjust the local contrast in the image so as to bring out the clear regions or objects in the image . Low-contrast images often result from poor or non-uniform lighting conditions, a limited dynamic range of the imaging sensor , or improper settings of the lens aperture.
This method usually increases the global contrast of many images, especially when the image is represented by a narrow range of intensity values. Through this adjustment, the 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.
Contrast sensitivity is typically expressed as the reciprocal of the threshold contrast for detection of a given pattern (i.e., 1 ÷ contrast threshold). [15] Using the results of a contrast sensitivity exam, a contrast sensitivity curve can be plotted, with spatial frequency on the horizontal, and contrast threshold on the vertical axis.
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.
[23] [24] The HDR display must have either a peak brightness of over 1000 cd/m 2 and a black level less than 0.05 cd/m 2 (a contrast ratio of at least 20,000:1) or a peak brightness of over 540 cd/m 2 and a black level less than 0.0005 cd/m 2 (a contrast ratio of at least 1,080,000:1).
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