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These blocks can then be subjected to discrete cosine transform (DCT) to calculate the frequency components, both horizontally and vertically. [1] The resulting block (the same size as the original block) is then pre-multiplied by the quantization scale code and divided element-wise by the quantization matrix, and rounding each resultant element.
The macroblock is a processing unit in image and video compression formats based on linear block transforms, typically the discrete cosine transform (DCT). A macroblock typically consists of 16×16 samples, and is further subdivided into transform blocks, and may be further subdivided into prediction blocks.
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.
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.
CCSDS 122.0 makes use of a three-level two-dimensional discrete wavelet transform (DWT) using a biorthogonal 9/7 tap filters, followed by a bit-plane encoder. It has some design commonalities with ICER and JPEG 2000 that use similar wavelet coding schemes. The transform (DWT) can be computed using either floating-point or integer arithmetic.
The raw image format Digital Negative (DNG) allows image data contained within to be compressed using JPEG XL. Starting in version 1.7.0.0 from June 2023, JPEG XL compression was included as part of the specification. [39] This created a basis for later use as part of "Expert RAW" in Samsung Galaxy smartphones and Apple's "ProRAW".
Set partitioning in hierarchical trees (SPIHT) [1] is an image compression algorithm that exploits the inherent similarities across the subbands in a wavelet decomposition of an image. The algorithm was developed by Brazilian engineer Amir Said with William A. Pearlman in 1996.
Transform coding is a type of data compression for "natural" data like audio signals or photographic images.The transformation is typically lossless (perfectly reversible) on its own but is used to enable better (more targeted) quantization, which then results in a lower quality copy of the original input (lossy compression).