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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.
An image scaled with nearest-neighbor scaling (left) and 2×SaI scaling (right) In computer graphics and digital imaging , image scaling refers to the resizing of a digital image. In video technology, the magnification of digital material is known as upscaling or resolution enhancement .
9-slice scaling (also known as Scale 9 grid, 9-slicing or 9-patch) is a 2D image resizing technique to proportionally scale an image by splitting it in a grid of nine parts. [ 1 ] The key idea is to prevent image scaling distortion by protecting the pixels defined in 4 parts (corners) of the image and scaling or repeating the pixels in the ...
This template creates a box with two to ten images arranged vertically or horizontally with captions for the entire box and each image. Template parameters [Edit template data] This template has custom formatting. Parameter Description Type Status Alignment align Sets text-wrapping around image box, where "none" places the box on the left edge with no text-wrapping, "center" places the box at ...
Scale the image to be no greater than the given width or height, keeping its aspect ratio. Scaling up (i.e. stretching the image to a greater size) is disabled when the image is framed. Link Link the image to a different resource, or to nothing. Alt Specify the alt text for the image. This is intended for visually impaired readers.
XSL-FO 1.1 refines the functionality for sizing of graphics to fit, with the ability to shrink to fit (but not grow to fit), as well as the ability to define specific scaling steps. In addition, the resulting scaling factor can be referenced for display (for example, to say in a figure caption, "image shown is 50% actual size").
Directional Cubic Convolution Interpolation (DCCI) is an edge-directed image scaling algorithm created by Dengwen Zhou and Xiaoliu Shen. [1] By taking into account the edges in an image, this scaling algorithm reduces artifacts common to other image scaling algorithms. For example, staircase artifacts on diagonal lines and curves are eliminated.
The following examples use the "thumb" or "frameless" options to set an image to the default size, with "upright" to scale the image larger or smaller than the default size. When using these options, a small image will never be scaled larger than its original size.