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Unsharp masking applied to lower part of image. Unsharp masking (USM) is an image sharpening technique, first implemented in darkroom photography, but now commonly used in digital image processing software. Its name derives from the fact that the technique uses a blurred, or "unsharp", negative image to create a mask of the original image. The ...
Image sharpening: original (top), image sharpened (bottom). Another form of image sharpening involves a form of contrast. This is done by finding the average color of the pixels around each pixel in a specified radius, and then contrasting that pixel from that average color. This effect makes the image seem clearer, seemingly adding details.
In digital photography, onboard camera software and image postprocessing tools such as Photoshop or GIMP offer various sharpening facilities, the most widely used of which is known as "unsharp mask" because the algorithm is derived from the eponymous analog processing method. In the example image, two light gray lines were drawn on a gray ...
The resulting image is larger than the original, and preserves all the original detail, but has (possibly undesirable) jaggedness. The diagonal lines of the "W", for example, now show the "stairway" shape characteristic of nearest-neighbor interpolation. Other scaling methods below are better at preserving smooth contours in the image.
The Luminosity mode is commonly used for image sharpening, because human vision is much more sensitive to fine-scale lightness contrast than color contrast. (See Contrast (vision)) Few editors other than Photoshop implement this same color space for their analogs of these blend modes. [3]
In image processing, a kernel, convolution matrix, or mask is a small matrix used for blurring, sharpening, embossing, edge detection, and more.This is accomplished by doing a convolution between the kernel and an image.
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