Advantages And Disadvantages Of Adaptive Histogram...

Advantages And Disadvantages Of Adaptive Histogram...

2.1.6 Histogram Equalization



The luminance histogram of a exemplary natural scene that has been linearly quantized is commonly highly skewed toward the darker levels; a majority of the pixels possess a luminance lower than the average. In similar images, detail in the darker regions is often not visible. One means of enhancing these types of images is a method called histogram modification, in which the original image is rescaled so that the histogram of the intensified image follows some desired form [6]. This method also assumes the detail carried by an image is related to the possibility of occurrence of each gray level. To maximize the detail, the transformation should redistribute the possibilities of occurrence of the gray level to make it identical. In this way, the contrast at every gray level is proportional to the altitude of the image histogram [7]. Several modifications of histogram equalization are also available which expansion its potential of contrast enhancement. Adaptive histogram equalization (AHE) [8] and Contrast limited adaptive histogram equalization (CLAHE) [9] belong to that classification which apply histogram ... Show more content on Helpwriting.net ...This is also as preparation of the next step where the histogram will be divided into two regions based on its average value. The stretched–histogram will provide a better pixel distribution of the image channels and thus gives a more accurate average value of the channel which represents the average value of the channel for the whole dynamic range. The equation (6) is used to stretch the histogram of respective color channel to the whole dynamic range. Pin and Pout are the input and output pixels, respectively, and imin, imax, omin, and omax are the minimum and maximum intensity level values for the input and output images,

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