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The pulse compression is based on FFT and IFFT algorithms.
The principle of the compression is based on prediction.
Karhunen-Loève (KL) compression is based on the canonical representation of a random process.
The compression is based on psychoacoustic models in which the precision of audio components that are less audible to the human ear are reduced.
Conventional CS theory, developed for image compression, is based on the representation of lattice data using the so-called first-generation wavelets (FGW) [5].
JPEG image compression is based on discrete cosine transform (DCT), which is one of the basic building blocks for JPEG compression [13, 14].
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Many existing works related to lossy-to-lossless multiresolution image compression are based on the lifting concept.
JPEG 2000 is an international standard for still image compression, which is based on wavelet transformation and the Daubechies 9/7 filter adopted for lossy compression.
The compression part is based on the Shape Adaptive DCT with ΔDC correction method.
Its video compression technology is based on H.264 Scalable Video Coding (SVC), which can be used to deploy high-quality video conferencing, even on constrained mobile networks.
But fractal compression, which is based on the iterated function system (IFS) proposed by Mandelbrot[1], is a relative new approach to image coding.
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