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The difference between a small and large Gaussian blur. In image processing, a Gaussian blur (also known as Gaussian smoothing) is the result of blurring an image by a Gaussian function (named after mathematician and scientist Carl Friedrich Gauss). It is a widely used effect in graphics software, typically to reduce image noise and
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.
A box blur (also known as a box linear filter) is a spatial domain linear filter in which each pixel in the resulting image has a value equal to the average value of its neighboring pixels in the input image. It is a form of low-pass ("blurring") filter. A 3 by 3 box blur ("radius 1") can be written as matrix
The term comes from the Japanese word boke (暈け/ボケ), which means "blur" or "haze", resulting in boke-aji (ボケ味), the "blur quality".This is derived as a noun form of the verb bokeru, which is written in several ways, [7] with additional meanings and nuances: 暈ける refers to being blurry, hazy or out-of-focus, whereas the 惚ける and 呆ける spellings refer to being mentally ...
The software applies a Gaussian blur to a copy of the original image and then compares it to the original. If the difference is greater than a user-specified threshold setting, the images are (in effect) subtracted. Digital unsharp masking is a flexible and powerful way to increase sharpness, especially in scanned images.
Miniature faking, also known as diorama effect or diorama illusion, is a process in which a photograph of a life-size location or object is made to look like a photograph of a miniature scale model.
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