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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 reduce detail.
The background image is used as the bottom layer, and the image with parts to be added are placed in a layer above that. Using an image layer mask , all but the parts to be merged is hidden from the layer, giving the impression that these parts have been added to the background layer.
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 ...
All detection techniques are based on modelling the background of the image, i.e. set the background and detect which changes occur. Defining the background can be very difficult when it contains shapes, shadows, and moving objects. In defining the background, it is assumed that the stationary objects could vary in color and intensity over time.
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Pixelization (British English, pixelisation) or mosaic processing is any technique used in editing images or video, whereby an image is blurred by displaying part or all of it at a markedly lower resolution. It is primarily used for censorship. The effect is a standard graphics filter, available in all but the most basic bitmap graphics editors.
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