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The contrast ranges from black at the weakest intensity to white at the strongest. [1] 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.
For example, the white point of an sRGB display is an x, y chromaticity of (0.3127, 0.3290), where x and y coordinates are used in the xyY space. ( u′ , v′ ) , the chromaticity in CIELUV , is a fairly perceptually uniform presentation of the chromaticity as (another than in CIE 1931) planar Euclidean shape.
In computing terminology, black-and-white is sometimes used to refer to a binary image consisting solely of pure black pixels and pure white ones; what would normally be called a black-and-white image, that is, an image containing shades of gray, is referred to in this context as grayscale. [2]
On the left, an intensity image of a cat. In the center, a gradient image in the x direction measuring horizontal change in intensity. On the right, a gradient image in the y direction measuring vertical change in intensity. Gray pixels have a small gradient; black or white pixels have a large gradient.
In image processing, computer vision and related fields, an image moment is a certain particular weighted average of the image pixels' intensities, or a function of such moments, usually chosen to have some attractive property or interpretation. Image moments are useful to describe objects after segmentation.
When converting an image from the PNG format to GIF, the image quality may suffer due to posterization if the PNG image has more than 256 colors. GIF intrinsically supports animated images. PNG supports animation only via unofficial extensions (see the section on animation, above). PNG images are less widely supported by older browsers.
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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