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  2. Template matching - Wikipedia

    en.wikipedia.org/wiki/Template_matching

    Template matching [1] is a technique in digital image processing for finding small parts of an image which match a template image. It can be used for quality control in manufacturing, [ 2 ] navigation of mobile robots , [ 3 ] or edge detection in images.

  3. 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 ...

  4. 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.

  5. Indexed color - Wikipedia

    en.wikipedia.org/wiki/Indexed_color

    A 2-bit indexed color image. The color of each pixel is represented by a number; each number (the index) corresponds to a color in the color table (the palette).. In computing, indexed color is a technique to manage digital images' colors in a limited fashion, in order to save computer memory and file storage, while speeding up display refresh and file transfers.

  6. Group 4 compression - Wikipedia

    en.wikipedia.org/wiki/Group_4_compression

    Group 4 compression is available in many proprietary image file formats as well as standardized formats such as TIFF, CALS, CIT (Intergraph Raster Type 24) and the PDF document format. G4 offers a small improvement over G3-2D by removing the end-of-line (EOL) codes. G3 and G4 compression both treat an image as a series of horizontal black ...

  7. Normalization (image processing) - Wikipedia

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

    max is the maximum value for color level in the input image within the selected kernel. min is the minimum value for color level in the input image within the selected kernel. [4] Local contrast stretching considers each range of color palate in the image (R, G, and B) separately, providing a set of minimum and maximum values for each color palate.

  8. 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 ...

  9. Pyramid (image processing) - Wikipedia

    en.wikipedia.org/wiki/Pyramid_(image_processing)

    These can be seen as a kind of image pyramid. Because those file format store the "large-scale" features first, and fine-grain details later in the file, a particular viewer displaying a small "thumbnail" or on a small screen can quickly download just enough of the image to display it in the available pixels—so one file can support many ...