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  2. 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.

  3. Edge-preserving smoothing - Wikipedia

    en.wikipedia.org/wiki/Edge-preserving_smoothing

    Anisotropic diffusion generates small conductance at the location of the edge of the image to prevent the heat flow over the edge, thus making the anisotropic diffusion filter edge-preserving. In the graph-based interpretation, the small conductance corresponds to a small weight of an edge of the graph describing a probability of a random walk ...

  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. File:Ilovepdf.svg - Wikipedia

    en.wikipedia.org/wiki/File:Ilovepdf.svg

    Main page; Contents; Current events; Random article; About Wikipedia; Contact us; Pages for logged out editors learn more

  6. Seam carving - Wikipedia

    en.wikipedia.org/wiki/Seam_carving

    Original image to be made narrower Scaling is undesirable because the castle is distorted. Cropping is undesirable because part of the castle is removed. Seam carving. Seam carving (or liquid rescaling) is an algorithm for content-aware image resizing, developed by Shai Avidan, of Mitsubishi Electric Research Laboratories (MERL), and Ariel Shamir, of the Interdisciplinary Center and MERL.

  7. Bilateral filter - Wikipedia

    en.wikipedia.org/wiki/Bilateral_filter

    Left: original image. Right: image processed with bilateral filter. A bilateral filter is a non-linear, edge-preserving, and noise-reducing smoothing filter for images. It replaces the intensity of each pixel with a weighted average of intensity values from nearby pixels. This weight can be based on a Gaussian distribution.