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The best image quality at a given compression rate (or bit rate) is the main goal of image compression, however, there are other important properties of image compression schemes: Scalability generally refers to a quality reduction achieved by manipulation of the bitstream or file (without decompression and re-compression).
The JPEG compression algorithm operates at its best on photographs and paintings of realistic scenes with smooth variations of tone and color. For web usage, where reducing the amount of data used for an image is important for responsive presentation, JPEG's compression benefits make JPEG popular.
An important image compression technique is the discrete cosine transform (DCT), a technique developed in the early 1970s. [16] DCT is the basis for JPEG, a lossy compression format which was introduced by the Joint Photographic Experts Group (JPEG) in 1992. [34]
An important development in digital image compression technology was the discrete cosine transform (DCT), a lossy compression technique first proposed by Nasir Ahmed in 1972. [26] DCT compression became the basis for JPEG, which was introduced by the Joint Photographic Experts Group in 1992. [27]
Composite image showing JPG and PNG image compression. Left side of the image is from a low-quality JPEG image, showing lossy artefacts; the right side is from a PNG image. In information technology, lossy compression or irreversible compression is the class of data compression methods that uses inexact approximations and partial data ...
JPEG XL beats AVIF for higher quality images, but AVIF will often outperform JPEG XL on low quality images in low-fidelity, high-appeal compression: low quality AVIF images will smooth out details and hide compression artifacts better, making them more visually appealing than JPEG XL images of the same size.
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The DCT-II is an important image compression technique. It is used in image compression standards such as JPEG, and video compression standards such as H.26x, MJPEG, MPEG, DV, Theora and Daala. There, the two-dimensional DCT-II of blocks are computed and the results are quantized and entropy coded.
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