enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. 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.

  3. Otsu's method - Wikipedia

    en.wikipedia.org/wiki/Otsu's_method

    hists is a 2D-histogram of grayscale value and neighborhood average grayscale value pair. total is the number of pairs in the given image.it is determined by the number of the bins of 2D-histogram at each direction. threshold is the threshold obtained.

  4. Unimodal thresholding - Wikipedia

    en.wikipedia.org/wiki/Unimodal_thresholding

    Most threshold selection algorithms assume that the intensity histogram is multi-modal; typically bimodal. However, some types of images are essentially unimodal since a much larger proportion of just one class of pixels (e.g. the background) is present in the image, and dominates the histogram. In such circumstances many of the standard ...

  5. Thresholding (image processing) - Wikipedia

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

    Histogram shape-based methods, where, for example, the peaks, valleys and curvatures of the smoothed histogram are analyzed. [3] Note that these methods, more than others, make certain assumptions about the image intensity probability distribution (i.e., the shape of the histogram),

  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. 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.

  8. 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.

  9. Plotting algorithms for the Mandelbrot set - Wikipedia

    en.wikipedia.org/wiki/Plotting_algorithms_for...

    This technique is used to good effect in the B&W images of Mandelbrot sets in the books "The Beauty of Fractals [9]" and "The Science of Fractal Images". [10] Here is a sample B&W image rendered using Distance Estimates: This is a B&W image of a portion of the Mandelbrot set rendered using Distance Estimates (DE)