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The DCT, and in particular the DCT-II, is often used in signal and image processing, especially for lossy compression, because it has a strong energy compaction property. [ 5 ] [ 6 ] In typical applications, most of the signal information tends to be concentrated in a few low-frequency components of the DCT.
Quantization, involved in image processing, is a lossy compression technique achieved by compressing a range of values to a single quantum (discrete) value. When the number of discrete symbols in a given stream is reduced, the stream becomes more compressible.
Unlike the lossy mode which is based on the DCT, the lossless coding process employs a simple predictive coding model called differential pulse-code modulation (DPCM). This is a model in which predictions of the sample values are estimated from the neighboring samples that are already coded in the image.
The term is much more commonly used in digital media and digital signal processing.The most widely used transform coding technique in this regard is the discrete cosine transform (DCT), [1] [2] proposed by Nasir Ahmed in 1972, [3] [4] and presented by Ahmed with T. Natarajan and K. R. Rao in 1974. [5]
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.
Image fusion based on the multi-scale transform is the most commonly used and promising technique. Laplacian pyramid transform, gradient pyramid-based transform, morphological pyramid transform and the premier ones, discrete wavelet transform, shift-invariant wavelet transform (SIDWT), and discrete cosine harmonic wavelet transform (DCHWT) are some examples of image fusion methods based on ...
As in still image coding, it is possible to apply a deblocking filter to the decoder output as post-processing. In motion-predicted video coding with a closed prediction loop, the encoder uses the decoder output as the prediction reference from which future frames are predicted. To that end, the encoder conceptually integrates a decoder.
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.