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  2. Gaussian blur - Wikipedia

    en.wikipedia.org/wiki/Gaussian_blur

    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.

  3. Boris Continuum Complete - Wikipedia

    en.wikipedia.org/wiki/Boris_Continuum_Complete

    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.

  4. Bilateral filter - Wikipedia

    en.wikipedia.org/wiki/Bilateral_filter

    GIMP implements a bilateral filter in its Filters → Blur tools; and it is called Selective Gaussian Blur. The free G'MIC plugin Repair → Smooth [bilateral] for GIMP adds more control. [7] A simple trick to efficiently implement a bilateral filter is to exploit Poisson-disk subsampling. [1]

  5. Spatial anti-aliasing - Wikipedia

    en.wikipedia.org/wiki/Spatial_anti-aliasing

    Gaussian plus differential function One might consider a Gaussian plus enough of its second derivative to flatten the top (in the frequency domain) or sharpen it up (in the spatial domain), as shown. Functions based on the Gaussian function are natural choices, because convolution with a Gaussian gives another Gaussian whether applied to x and ...

  6. Gaussian filter - Wikipedia

    en.wikipedia.org/wiki/Gaussian_filter

    In Image processing, each element in the matrix represents a pixel attribute such as brightness or color intensity, and the overall effect is called Gaussian blur. The Gaussian filter is non-causal, which means the filter window is symmetric about the origin in the time domain. This makes the Gaussian filter physically unrealizable.

  7. Kernel (image processing) - Wikipedia

    en.wikipedia.org/wiki/Kernel_(image_processing)

    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.

  8. Difference of Gaussians - Wikipedia

    en.wikipedia.org/wiki/Difference_of_Gaussians

    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.

  9. Box blur - Wikipedia

    en.wikipedia.org/wiki/Box_blur

    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