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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.
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.
Increase contrast of yellow objects A 25 Increase contrast of brown objects B2 58 Increase contrast of red objects; commonly known as B C5 47 Photograph blue as white; replaces C4 (#49) with a comparable filter factor as updated A and B2 F 29 Blueprints; photograph red as white Three-color separation A 25
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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 ...
Given a partial image, it is possible to extract a much fuller picture. Properly pre-processing the image with a simple Auto Threshold grayscale to binary converter will give the skeletonization function an easier time thinning. The higher contrast ratio will allow the lines to joined in a more accurate manner.