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  2. Color moments - Wikipedia

    en.wikipedia.org/wiki/Color_moments

    Computing the features - Use the color moments formulae in order to compute the first three moments for each of the color channels in the image. For example, if the HSV color space is used, this means that for each of the images, 9 features in total will be computed (the first three order moments for the Hue, Saturation, and Value channels).

  3. Standard deviation - Wikipedia

    en.wikipedia.org/wiki/Standard_deviation

    The mean and the standard deviation of a set of data are descriptive statistics usually reported together. In a certain sense, the standard deviation is a "natural" measure of statistical dispersion if the center of the data is measured about the mean. This is because the standard deviation from the mean is smaller than from any other point.

  4. Image color transfer - Wikipedia

    en.wikipedia.org/wiki/Image_color_transfer

    Newer statistic-based algorithms deal with this problem. An example of such algorithm is one that adjusts the mean and the standard deviation of each of the source image channels to match those of the corresponding reference image channels. This adjustment process is typically performed in the Lαβ or Lab color spaces. [2]

  5. 68–95–99.7 rule - Wikipedia

    en.wikipedia.org/wiki/68–95–99.7_rule

    For an approximately normal data set, the values within one standard deviation of the mean account for about 68% of the set; while within two standard deviations account for about 95%; and within three standard deviations account for about 99.7%. Shown percentages are rounded theoretical probabilities intended only to approximate the empirical ...

  6. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    If is a standard normal deviate, then = + will have a normal distribution with expected value and standard deviation . This is equivalent to saying that the standard normal distribution Z {\textstyle Z} can be scaled/stretched by a factor of σ {\textstyle \sigma } and shifted by μ {\textstyle \mu } to yield a different normal distribution ...

  7. Land cover maps - Wikipedia

    en.wikipedia.org/wiki/Land_cover_maps

    The decision boundaries are formed by calculating the mean distance between class pixels and using the standard deviation of the generated training datasets to generate a parallelepiped box. Mahalanobis distance [5] – A system of classification that uses the Euclidean distance algorithm to assign land cover classes from a set of training ...

  8. Root mean square deviation - Wikipedia

    en.wikipedia.org/wiki/Root_mean_square_deviation

    In some disciplines, the RMSD is used to compare differences between two things that may vary, neither of which is accepted as the "standard". For example, when measuring the average difference between two time series x 1 , t {\displaystyle x_{1,t}} and x 2 , t {\displaystyle x_{2,t}} , the formula becomes

  9. MacAdam ellipse - Wikipedia

    en.wikipedia.org/wiki/MacAdam_ellipse

    In the study of color vision, a MacAdam ellipse is roughly a region on a chromaticity diagram which contains all colors which are indistinguishable to the average human eye, from the color at the center of the ellipse. Specifically, it is the standard deviation of a number of experimental color matches to the central color.