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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.
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.
OpenCV (Open Source Computer Vision Library) is a library of programming functions mainly for real-time computer vision. [2] Originally developed by Intel, it was later supported by Willow Garage, then Itseez (which was later acquired by Intel [3]). The library is cross-platform and licensed as free and open-source software under Apache License ...
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 ...
Luminance HDR/QtPfsGui is a free (open-source) HDR-workflow software for Linux, Windows and Mac OS X based around the pfstools package; LDR tonemapping is a free (open-source) tonemapper for low dynamic range images (a.k.a. "pseudo-HDR") Atlas is a free (open-source) port of the pfstmo tone mapping operators to Adobe After Effects
The SSIM index is a full reference metric; in other words, the measurement or prediction of image quality is based on an initial uncompressed or distortion-free image as reference. SSIM is a perception -based model that considers image degradation as perceived change in structural information, while also incorporating important perceptual ...
Consider a grayscale input image X. It has a probability density function p r (r), where r is a grayscale value, and p r (r) is the probability of that value. This probability can easily be computed from the histogram of the image by
In image processing, a kernel, convolution matrix, or mask is a small matrix used for blurring, sharpening, embossing, edge detection, and more.This is accomplished by doing a convolution between the kernel and an image.