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  2. Histogram equalization - Wikipedia

    en.wikipedia.org/wiki/Histogram_equalization

    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. There are two ways to think about and implement histogram equalization, either as image change or as palette change.

  3. Adaptive histogram equalization - Wikipedia

    en.wikipedia.org/.../Adaptive_histogram_equalization

    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.

  4. Histogram matching - Wikipedia

    en.wikipedia.org/wiki/Histogram_matching

    An example of histogram matching. In image processing, histogram matching or histogram specification is the transformation of an image so that its histogram matches a specified histogram. [1] The well-known histogram equalization method is a special case in which the specified histogram is uniformly distributed. [2]

  5. Local binary patterns - Wikipedia

    en.wikipedia.org/wiki/Local_binary_patterns

    Multi-block LBP: the image is divided into many blocks, a LBP histogram is calculated for every block and concatenated as the final histogram. Volume Local Binary Pattern(VLBP): [11] VLBP looks at dynamic texture as a set of volumes in the (X,Y,T) space where X and Y denote the spatial coordinates and T denotes the frame index. The neighborhood ...

  6. Image segmentation - Wikipedia

    en.wikipedia.org/wiki/Image_segmentation

    Histogram-based methods are very efficient compared to other image segmentation methods because they typically require only one pass through the pixels. In this technique, a histogram is computed from all of the pixels in the image, and the peaks and valleys in the histogram are used to locate the clusters in the image. [1]

  7. Balanced histogram thresholding - Wikipedia

    en.wikipedia.org/wiki/Balanced_histogram...

    In image processing, the balanced histogram thresholding method (BHT), [1] is a very simple method used for automatic image thresholding.Like Otsu's Method [2] and the Iterative Selection Thresholding Method, [3] this is a histogram based thresholding method.

  8. OpenCV - Wikipedia

    en.wikipedia.org/wiki/OpenCV

    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 ...

  9. Talk:Histogram equalization - Wikipedia

    en.wikipedia.org/wiki/Talk:Histogram_equalization

    The notation h(v) is incorectly used several times. h(v) would be the new values of the histogram for that specific pixel value, but it is used when calculating the actual new pixel value of the transformed image resulted from the process of histogram equalization. A.Roman2104 02:20, 27 January 2023 (UTC)