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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. Image scaling - Wikipedia

    en.wikipedia.org/wiki/Image_scaling

    When scaling a vector graphic image, the graphic primitives that make up the image can be scaled using geometric transformations with no loss of image quality. When scaling a raster graphics image, a new image with a higher or lower number of pixels must be generated. In the case of decreasing the pixel number (scaling down), this usually ...

  4. Vector graphics - Wikipedia

    en.wikipedia.org/wiki/Vector_graphics

    This vector-based (SVG format) image of a round four-color swirl displays several unique features of vector graphics versus raster graphics: there is no aliasing along the rounded edge (which would result in digital artifacts in a raster graphic), the color gradients are all smooth, and the user can resize the image infinitely without losing ...

  5. Vector graphics editor - Wikipedia

    en.wikipedia.org/wiki/Vector_graphics_editor

    A vector graphic editor is a computer program that enables its users to create, compose and edit images with the use of mathematical and geometrical commands rather than individual pixels. This software is used in creating high-definition vector graphic images that can be scaled indefinitely without losing their quality.

  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. Help:Pictures - Wikipedia

    en.wikipedia.org/wiki/Help:Pictures

    The underlying image's native dimensions are 3916×1980, and the coordinates are given in these dimensions rather than in the 300px resizing. As described in the image map documentation, regions can be specified as circles, rectangles, and arbitrary polygons, and the blue "i" icon can be moved or suppressed.

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