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  2. Histogram equalization - Wikipedia

    en.wikipedia.org/wiki/Histogram_equalization

    So in theory, if the histogram equalization function is known, then the original histogram can be recovered. The calculation is not computationally intensive. A disadvantage of the method is that it is indiscriminate. It may increase the contrast of background noise, while decreasing the usable signal.

  3. Adaptive histogram equalization - Wikipedia

    en.wikipedia.org/wiki/Adaptive_histogram...

    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

    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 .

  5. Histogram of oriented gradients - Wikipedia

    en.wikipedia.org/wiki/Histogram_of_oriented...

    The histogram of oriented gradients (HOG) is a feature descriptor used in computer vision and image processing for the purpose of object detection. The technique counts occurrences of gradient orientation in localized portions of an image.

  6. 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 ...

  7. Otsu's method - Wikipedia

    en.wikipedia.org/wiki/Otsu's_method

    Otsu's method performs well when the histogram has a bimodal distribution with a deep and sharp valley between the two peaks. [ 6 ] Like all other global thresholding methods, Otsu's method performs badly in case of heavy noise, small objects size, inhomogeneous lighting and larger intra-class than inter-class variance. [ 7 ]

  8. Normalization (image processing) - Wikipedia

    en.wikipedia.org/wiki/Normalization_(image...

    In image processing, normalization is a process that changes the range of pixel intensity values. Applications include photographs with poor contrast due to glare, for example.

  9. 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.