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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.
Existing JPEG files can be compressed a bit more, with no additional loss in quality, using jpegtran -optimize. This results in a smaller file, but the compression is slower. Jpegtran is part of libjpeg. A package called littleutils contains a script called opt-jpg that automates JPEG optimization, using jpegtran as the underlying engine.
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:
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.
While data reduction (compression, be it lossy or lossless) is a main goal of transform coding, it also allows other goals: one may represent data more accurately for the original amount of space [5] – for example, in principle, if one starts with an analog or high-resolution digital master, an MP3 file of a given size should provide a better ...
If the size of the text on your screen is too hard to read comfortably, you can easily change it. Learn how to make the font bigger or smaller on your web browser.