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  2. Gaussian blur - Wikipedia

    en.wikipedia.org/wiki/Gaussian_blur

    Gaussian blurring is commonly used when reducing the size of an image. When downsampling an image, it is common to apply a low-pass filter to the image prior to resampling. This is to ensure that spurious high-frequency information does not appear in the downsampled image . Gaussian blurs have nice properties, such as having no sharp edges, and ...

  3. Comparison gallery of image scaling algorithms - Wikipedia

    en.wikipedia.org/wiki/Comparison_gallery_of...

    The resulting image is larger than the original, and preserves all the original detail, but has (possibly undesirable) jaggedness. The diagonal lines of the "W", for example, now show the "stairway" shape characteristic of nearest-neighbor interpolation. Other scaling methods below are better at preserving smooth contours in the image.

  4. Smoothing - Wikipedia

    en.wikipedia.org/wiki/Smoothing

    In image processing and computer vision, smoothing ideas are used in scale space representations. The simplest smoothing algorithm is the "rectangular" or "unweighted sliding-average smooth". This method replaces each point in the signal with the average of "m" adjacent points, where "m" is a positive integer called the "smooth width".

  5. Sumo Paint - Wikipedia

    en.wikipedia.org/wiki/Sumo_Paint

    Sumopaint, also written as Sumo Paint is a free painting and drawing web application similar to Adobe Photoshop. [1] [2] [3] Sumopaint has web-based "paint" features similar in some respects to Pixlr. [4] It was originally created in 2008 by Sumo Limited. [5]

  6. Pyramid (image processing) - Wikipedia

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

    Visual representation of an image pyramid with 5 levels. Pyramid, or pyramid representation, is a type of multi-scale signal representation developed by the computer vision, image processing and signal processing communities, in which a signal or an image is subject to repeated smoothing and subsampling.

  7. Perlin noise - Wikipedia

    en.wikipedia.org/wiki/Perlin_noise

    Two-dimensional slice through 3D Perlin noise at z = 0. Perlin noise is a type of gradient noise developed by Ken Perlin in 1983. It has many uses, including but not limited to: procedurally generating terrain, applying pseudo-random changes to a variable, and assisting in the creation of image textures.