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Like any resampling operation, changing image size and bit depth are lossy in all cases of downsampling, such as 30-bit to 24-bit or 24-bit to 8-bit palette-based images. While increasing bit depth is usually lossless, increasing image size can introduce aliasing or other undesired artifacts.
Image scaling can be interpreted as a form of image resampling or image reconstruction from the view of the Nyquist sampling theorem.According to the theorem, downsampling to a smaller image from a higher-resolution original can only be carried out after applying a suitable 2D anti-aliasing filter to prevent aliasing artifacts.
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.
optimisation of the Huffman coding layer of a JPEG file to increase compression, conversion between progressive and sequential JPEG formats, conversion between Huffman and arithmetic coding in the entropy coding layer. [5] [6] [7] These transformations are each completely lossless and reversible. The transformations on the image data comprise:
Since most JPEGs in Wikipedia will be rescaled anyway before appearing on pages, a quality setting of 95 is appropriate. (Settings above 95 increase size dramatically for little improvement in image quality.) JPEG compression works better on slightly blurred images, so don't sharpen the images too much as it will result in a higher footprint.
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