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  2. Pixelization - Wikipedia

    en.wikipedia.org/wiki/Pixelization

    Pixelization (in 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.

  3. 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.

  4. Edge enhancement - Wikipedia

    en.wikipedia.org/wiki/Edge_enhancement

    Edge enhancement is an image processing filter that enhances the edge contrast of an image or video in an attempt to improve its acutance (apparent sharpness).. The filter works by identifying sharp edge boundaries in the image, such as the edge between a subject and a background of a contrasting color, and increasing the image contrast in the area immediately around the edge.

  5. Unsharp masking - Wikipedia

    en.wikipedia.org/wiki/Unsharp_masking

    For image processing, deconvolution is the process of approximately inverting the process that caused an image to be blurred. Specifically, unsharp masking is a simple linear image operation—a convolution by a kernel that is the Dirac delta minus a gaussian blur kernel.

  6. Image scaling - Wikipedia

    en.wikipedia.org/wiki/Image_scaling

    Image scaling can be interpreted as a form of image resampling or image reconstruction from the view of the Nyquist sampling theorem.According to the theorem, downsampling to a smaller image from a higher-resolution original can only be carried out after applying a suitable 2D anti-aliasing filter to prevent aliasing artifacts.

  7. 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.