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  2. Wikipedia:Autosizing images - Wikipedia

    en.wikipedia.org/wiki/Wikipedia:Autosizing_images

    upright=0.8 – scales the image to approximately 80% of the user's default size (20% smaller) upright=1.2 – scales the image to approximately 120% of the user's default size (20% larger) left – shifts the image to the left margin; right – shifts the image to the right margin; center – shifts the image to center between left/right margins

  3. Image editing - Wikipedia

    en.wikipedia.org/wiki/Image_editing

    Image sharpening: original (top), image sharpened (bottom). Another form of image sharpening involves a form of contrast. This is done by finding the average color of the pixels around each pixel in a specified radius, and then contrasting that pixel from that average color. This effect makes the image seem clearer, seemingly adding details.

  4. 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.

  5. 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 ...

  6. Wikipedia:Basic bitmap image editing - Wikipedia

    en.wikipedia.org/wiki/Wikipedia:Basic_bitmap...

    The image that you see on the right would be over 500 pixels wide if it were simply to be uploaded. There are several things that can be done about a very large image. If it is a scanned image, it can be rescanned at a lower resolution. If however the image is digital it must be either resized or cropped.

  7. 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.

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