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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. Channel (digital image) - Wikipedia

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

   Color digital images are made of pixels, and pixels are made of combinations of primary colors represented by a series of code. 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.

4. List of monochrome and RGB color formats - Wikipedia

   en.wikipedia.org/wiki/List_of_monochrome_and_RGB...

   For each unique palette, an image color test chart and sample image (truecolor original follows) rendered with that palette (without dithering) are given. The test chart shows the full 256 levels of the red, green, and blue (RGB) primary colors and cyan, magenta, and yellow complementary colors, along with a full 256-level grayscale.

5. Dilation (morphology) - Wikipedia

   en.wikipedia.org/wiki/Dilation_(morphology)

   Example of dilation on a grayscale image using a 5x5 flat structuring element. The top figure demonstrates the application of the structuring element window to the individual pixels of the original image. The bottom figure shows the resulting dilated image. It is common to use flat structuring elements in morphological applications.

6. 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.

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8. Erosion (morphology) - Wikipedia

   en.wikipedia.org/wiki/Erosion_(morphology)

   Erosion (usually represented by ⊖) is one of two fundamental operations (the other being dilation) in morphological image processing from which all other morphological operations are based. It was originally defined for binary images, later being extended to grayscale images, and subsequently to complete lattices.

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