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  2. Normalization (image processing) - Wikipedia

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

    Applications include photographs with poor contrast due to glare, for example. Normalization is sometimes called contrast stretching or histogram stretching. In more general fields of data processing, such as digital signal processing, it is referred to as dynamic range expansion. [1]

  3. Histogram equalization - Wikipedia

    en.wikipedia.org/wiki/Histogram_equalization

    For example, if applied to 8-bit image displayed with 8-bit gray-scale palette it will further reduce color depth (number of unique shades of gray) of the image. 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.

  4. 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.

  5. 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]

  6. Histogram - Wikipedia

    en.wikipedia.org/wiki/Histogram

    The total area of a histogram used for probability density is always normalized to 1. If the length of the intervals on the x-axis are all 1, then a histogram is identical to a relative frequency plot. Histograms are sometimes confused with bar charts. In a histogram, each bin is for a different range of values, so altogether the histogram ...

  7. Sturges's rule - Wikipedia

    en.wikipedia.org/wiki/Sturges's_rule

    Sturges's rule [1] is a method to choose the number of bins for a histogram.Given observations, Sturges's rule suggests using ^ = + ⁡ bins in the histogram. This rule is widely employed in data analysis software including Python [2] and R, where it is the default bin selection method.

  8. This is the 1 type of stretch you should do before every workout

    www.aol.com/news/1-type-stretch-every-workout...

    Dynamic stretching is best to warm up before a workout to increase blood flow, reduce injury risk and increase flexibility. 5 examples of dynamic stretches.

  9. Image histogram - Wikipedia

    en.wikipedia.org/wiki/Image_histogram

    Histogram equalization is a popular example of these algorithms. Improvements in picture brightness and contrast can thus be obtained. In the field of computer vision, image histograms can be useful tools for thresholding. Because the information contained in the graph is a representation of pixel distribution as a function of tonal variation ...