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  2. Harris corner detector - Wikipedia

    en.wikipedia.org/wiki/Harris_corner_detector

    If we use Harris corner detector in a color image, the first step is to convert it into a grayscale image, which will enhance the processing speed. The value of the gray scale pixel can be computed as a weighted sums of the values R, B and G of the color image, {,,}, where, e.g.,

  3. Top-hat transform - Wikipedia

    en.wikipedia.org/wiki/Top-hat_transform

    In mathematical morphology and digital image processing, a top-hat transform is an operation that extracts small elements and details from given images.There exist two types of top-hat transform: the white top-hat transform is defined as the difference between the input image and its opening by some structuring element, while the black top-hat transform is defined dually as the difference ...

  4. Normalization (image processing) - Wikipedia

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

    Often, the motivation is to achieve consistency in dynamic range for a set of data, signals, or images to avoid mental distraction or fatigue. For example, a newspaper will strive to make all of the images in an issue share a similar range of grayscale. Normalization transforms an n-dimensional grayscale image : {} {,..

  5. Channel (digital image) - Wikipedia

    en.wikipedia.org/wiki/Channel_(digital_image)

    A channel in this context is the grayscale image of the same size as a color image, [citation needed] made of just one of these primary colors. For instance, an image from a standard digital camera will have a red, green and blue channel. A grayscale image has just one channel.

  6. Grayscale - Wikipedia

    en.wikipedia.org/wiki/Grayscale

    Grayscale images are distinct from one-bit bi-tonal black-and-white images, which, in the context of computer imaging, are images with only two colors: black and white (also called bilevel or binary images). Grayscale images have many shades of gray in between. Grayscale images can be the result of measuring the intensity of light at each pixel ...

  7. Histogram matching - Wikipedia

    en.wikipedia.org/wiki/Histogram_matching

    It has a probability density function p r (r), where r is a grayscale value, and p r (r) is the probability of that value. This probability can easily be computed from the histogram of the image by = Where n j is the frequency of the grayscale value r j, and n is the total number of pixels in the image.

  8. 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.

  9. Quantization (image processing) - Wikipedia

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

    This technique is commonly used for simplifying images, reducing storage requirements, and facilitating processing operations. In grayscale quantization, an image with N intensity levels is converted into an image with a reduced number of levels, typically L levels, where L<N. The process involves mapping each pixel's original intensity value ...