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From left to right: an original photo with no bokeh or blur; the same photo with synthetic bokeh effect applied to its background; the same photo with Gaussian blur applied to its background Bokeh can be simulated by convolving the image with a kernel that corresponds to the image of an out-of-focus point source taken with a real camera.
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.
Consequently, the foreground and background are often blurred, with the blur increasing with distance above or below the center of the image. In a photograph of a full-size scene, the DoF is considerably greater; in some cases, it is difficult to have much of the scene outside the DoF, even at the lens's maximum aperture. Thus a difference in ...
Bokeh, the aesthetic quality of the out-of-focus parts of an image; Box blur, a graphic-art effect; Defocus aberration, blurring of an image due to incorrect focus; Gaussian blur, a graphic-art effect; Motion blur, blurring of an image due to movement of the subject or imaging system
The points in focus (2) project points onto the image plane (5), but points at different distances (1 and 3) project blurred images, or circles of confusion. Decreasing the aperture size (4) reduces the size of the blur spots for points not in the focused plane, so that the blurring is imperceptible, and all points are within the DOF.
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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