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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.
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]
Many of the techniques of digital image processing, or digital picture processing as it often was called, were developed in the 1960s, at Bell Laboratories, the Jet Propulsion Laboratory, Massachusetts Institute of Technology, University of Maryland, and a few other research facilities, with application to satellite imagery, wire-photo standards conversion, medical imaging, videophone ...
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 ...
5. DCT is performed on each block in the chosen coefficient sets. These coefficient sets are chosen to inquire about the imperceptibility and robustness of algorithms equally. 6. Scramble the fingerprint image to gain the scrambled watermark WS (i, j). 7. Re-formulate the scrambled watermark image into a vector of zeros and ones. 8.
The DCT is the most widely used data compression transformation, the basis for most digital media standards (image, video and audio) and commonly used in digital signal processing. He also described the discrete sine transform (DST), which is related to the DCT.
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.