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  2. Histogram - Wikipedia

    en.wikipedia.org/wiki/Histogram

    The intervals are placed together in order to show that the data represented by the histogram, while exclusive, is also contiguous. (E.g., in a histogram it is possible to have two connecting intervals of 10.5–20.5 and 20.5–33.5, but not two connecting intervals of 10.5–20.5 and 22.5–32.5.

  3. Image histogram - Wikipedia

    en.wikipedia.org/wiki/Image_histogram

    By looking at the histogram for a specific image a viewer will be able to judge the entire tonal distribution at a glance. Image histograms are present on many modern services. Photographers can use them as an aid to show the distribution of tones captured, and whether image detail has been lost to blown-out highlights or blacked-out shadows. [2]

  4. Chart - Wikipedia

    en.wikipedia.org/wiki/Chart

    A histogram consists of tabular frequencies, shown as adjacent rectangles, erected over discrete intervals (bins), with an area equal to the frequency of the observations in the interval; first introduced by Karl Pearson. [3] A bar chart is a chart with rectangular bars with lengths proportional to the values that they represent. The bars can ...

  5. Frequency (statistics) - Wikipedia

    en.wikipedia.org/wiki/Frequency_(statistics)

    It is a way of showing unorganized data notably to show results of an election, income of people for a certain region, sales of a product within a certain period, student loan amounts of graduates, etc. Some of the graphs that can be used with frequency distributions are histograms, line charts, bar charts and pie charts. Frequency ...

  6. Scott's rule - Wikipedia

    en.wikipedia.org/wiki/Scott's_Rule

    Scott's rule is a method to select the number of bins in a histogram. [1] Scott's rule is widely employed in data analysis software including R , [ 2 ] Python [ 3 ] and Microsoft Excel where it is the default bin selection method.

  7. 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.

  8. V-optimal histograms - Wikipedia

    en.wikipedia.org/wiki/V-optimal_histograms

    A v-optimal histogram is based on the concept of minimizing a quantity which is called the weighted variance in this context. [1] This is defined as = =, where the histogram consists of J bins or buckets, n j is the number of items contained in the jth bin and where V j is the variance between the values associated with the items in the jth bin.

  9. File:Histogram example.svg - Wikipedia

    en.wikipedia.org/wiki/File:Histogram_example.svg

    Histogram; View more global usage of this file. Metadata. This file contains additional information, probably added from the digital camera or scanner used to create ...