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  2. 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]

  3. Bag-of-words model in computer vision - Wikipedia

    en.wikipedia.org/wiki/Bag-of-words_model_in...

    Pyramid match kernel [13] is a fast algorithm (linear complexity instead of classic one in quadratic complexity) kernel function (satisfying Mercer's condition) which maps the BoW features, or set of features in high dimension, to multi-dimensional multi-resolution histograms. An advantage of these multi-resolution histograms is their ability ...

  4. 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 ]

  5. 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.

  6. Image color transfer - Wikipedia

    en.wikipedia.org/wiki/Image_color_transfer

    An example of an algorithm that employs the statistical properties of the images is histogram matching. This is a classic algorithm for color transfer, but it can suffer from the problem that it is too precise so that it copies very particular color quirks from the target image, rather than the general color characteristics, giving rise to ...

  7. 12 reasons you aren't losing weight even though you're eating ...

    www.aol.com/12-reasons-arent-losing-weight...

    8. You're getting older. As you age, losing weight becomes harder for several reasons. One is that as you age, you lose lean muscle—about three to eight percent per decade, starting as early as ...

  8. Scale-invariant feature transform - Wikipedia

    en.wikipedia.org/wiki/Scale-invariant_feature...

    An orientation histogram with 36 bins is formed, with each bin covering 10 degrees. Each sample in the neighboring window added to a histogram bin is weighted by its gradient magnitude and by a Gaussian-weighted circular window with a that is 1.5 times that of the scale of the keypoint. The peaks in this histogram correspond to dominant ...

  9. 'Let's see what happens': Trump (reluctantly) picks ex-critic ...

    www.aol.com/lets-see-happens-trump-picks...

    Trump appeared to suggest he was appointing Ortagus only because she has strong support among his fellow Republicans. “These things usually don’t work out,” Trump said, “but she has strong ...