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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
With basic techniques, e.g., a tool such as Adobe Photoshop's Lens Blur filter, [9] using sharpness gradients extending from the middle of the image to the top and bottom, the effect is quite similar to that obtained using lens tilt. The simple techniques have limitations similar to those of lens tilt.
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 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.
A demonstration of the effect of a neutral density filter. Note that the photograph was exposed for the view through the filter, and thus the remainder of the scene is overexposed. If the exposure had instead been set for the unfiltered background, it would appear properly exposed while the view through the filter would be dark. A set of ND filters
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.
The Photoshop and illusions.hu flavors also produce the same result when the top layer is pure white (the differences between these two are in how one interpolates between these 3 results). These three results coincide with gamma correction of the bottom layer with γ=2 (for top black), unchanged bottom layer (or, what is the same, γ=1; for ...
It may also use multiple samples for effects like depth of field and motion blur. If evenly-spaced ray directions or times are used for each of these features, many rays are required, and some aliasing will remain. Cook-style, stochastic, or Monte Carlo ray tracing avoids this problem by using random sampling instead of evenly-spaced samples.
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