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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 .
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.
It is easier to rasterize a vector image than to vectorize a raster image; how to go about vectorizing a raster image is the focus of much research in the field of computer vision. Vector images can be modified more easily because they contain descriptions of the shapes for easy rearrangement.
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.
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 ...
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
This makes it useful for scaling the details in faces, and in particular eyes. xBRZ is optimized for multi-core CPUs and 64-bit architectures and shows 40–60% better performance than HQx even when running on a single CPU core only. [citation needed] It supports scaling images with an alpha channel, and scaling by integer factors from 2× up ...
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