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Image compression is a type of data compression applied to digital images, to reduce their cost for storage or transmission. Algorithms may take advantage of visual perception and the statistical properties of image data to provide superior results compared with generic data compression methods which are used for other digital data.
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 ...
In information technology, lossy compression or irreversible compression is the class of data compression methods that uses inexact approximations and partial data discarding to represent the content. These techniques are used to reduce data size for storing, handling, and transmitting content. The different versions of the photo of the cat on ...
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".
Image sizes on Wikipedia can be determined by doing the following: Go to the image page by clicking on the image thumbnail. Under the image there should be a set of numbers in the form "NNNNxMMMM." This is the size of the image in pixels. If these numbers do not appear, then the image is smaller than the limit you specified for display in the ...
An image file format is a file format for a digital image. There are many formats that can be used, such as JPEG, PNG, and GIF. Most formats up until 2022 were for storing 2D images, not 3D ones. The data stored in an image file format may be compressed or uncompressed. If the data is compressed, it may be done so using lossy compression or ...
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