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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 same differencing principle is used in the unsharp-masking tool in many digital-imaging software packages, such as Adobe Photoshop and GIMP. [1] 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 ...
Boris Continuum Complete is a special effects Plug-in package that works in conjunction with Adobe Creative Suite, including CS6, Avid editing and finishing systems such as: Sony Vegas Pro, and Apple Final Cut Pro.
OBS Studio (also Open Broadcaster Software or OBS, for short) [8] is a free and open-source, cross-platform screencasting and streaming app. It is available for Windows, macOS, Linux distributions, and BSD. The OBS Project raises funds on Open Collective and Patreon. [9] [10]
The response value of the Gaussian filter at this cut-off frequency equals exp(−0.5) ≈ 0.607. However, it is more common to define the cut-off frequency as the half power point: where the filter response is reduced to 0.5 (−3 dB) in the power spectrum, or 1/ √ 2 ≈ 0.707 in the amplitude spectrum (see e.g. Butterworth filter).
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 algorithm can also be used to obtain an approximation of the Laplacian of Gaussian when the ratio of size 2 to size 1 is roughly equal to 1.6. [3] The Laplacian of Gaussian is useful for detecting edges that appear at various image scales or degrees of image focus. The exact values of sizes of the two kernels that are used to approximate ...
A number of optimizations can be applied when implementing the box blur of a radius r and N pixels: [6] The box blur is a separable filter, so that only two 1D passes of averaging 2 r + 1 pixels will be needed, one horizontal and one vertical, for each pixel.