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  2. 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 ...

  3. 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.,

  4. Fractal compression - Wikipedia

    en.wikipedia.org/wiki/Fractal_compression

    2 triangles, example to show how fractal compression works. Fractal compression is a lossy compression method for digital images, based on fractals.The method is best suited for textures and natural images, relying on the fact that parts of an image often resemble other parts of the same image. [1]

  5. Histogram equalization - Wikipedia

    en.wikipedia.org/wiki/Histogram_equalization

    The above describes histogram equalization on a grayscale image. However it can also be used on color images by applying the same method separately to the Red, Green and Blue components of the RGB color values of the image.

  6. Thresholding (image processing) - Wikipedia

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

    The simplest thresholding methods replace each pixel in an image with a black pixel if the image intensity , is less than a fixed value called the threshold , or a white pixel if the pixel intensity is greater than that threshold. In the example image on the right, this results in the dark tree becoming completely black, and the bright snow ...

  7. 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 : {} {,..

  8. Otsu's method - Wikipedia

    en.wikipedia.org/wiki/Otsu's_method

    One limitation of the Otsu’s method is that it cannot segment weak objects as the method searches for a single threshold to separate an image into two classes, namely, foreground and background, in one shot. Because the Otsu’s method looks to segment an image with one threshold, it tends to bias toward the class with the large variance. [14]

  9. Hough transform - Wikipedia

    en.wikipedia.org/wiki/Hough_transform

    The Hough transform is a feature extraction technique used in image analysis, computer vision, pattern recognition, and digital image processing. [1] [2] The purpose of the technique is to find imperfect instances of objects within a certain class of shapes by a voting procedure.