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Image scaling. 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 . When scaling a vector graphic image, the graphic primitives that make up the image can be scaled using geometric ...
For magnifying computer graphics with low resolution and few colors (usually from 2 to 256 colors), better results will be achieved by pixel art scaling algorithms such as hqx or xbr. These produce sharp edges and maintain high level of detail. Unfortunately due to the standardized size of 218x80 pixels, the "Wiki" image cannot use HQ4x or ...
Resizing an animated GIF image will significantly reduce its quality, without any reduction of download time. When there are two or more "size" options of the same type, only the last one is valid. However, if both an upright and an absolute size are used together, the absolute size always takes precedence, regardless of where it appears in the ...
Lanczos filtering and Lanczos resampling are two applications of a mathematical formula. It can be used as a low-pass filter or used to smoothly interpolate the value of a digital signal between its samples. In the latter case, it maps each sample of the given signal to a translated and scaled copy of the Lanczos kernel, which is a sinc ...
The available values for thumbnail size in Preferences (on the Appearance tab) are 120px, 150px, 180px, 200px, 220px (default), 250px, 300px, and 400px. As explained at Wikipedia:Extended image syntax § Size, upright=Factor will "adjust a thumbnail's size to Factor times the default thumbnail size, rounding the result to the nearest multiple of 10".
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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