Discrete Cosine Transform

Part of the The Kluwer International Series in Engineering and Computer Science book series (SECS, volume 376)


Moving continuous tone images are represented as a sequence of “frames”. A frame is a two-dimensional array of pixel values in one “plane” for black and white images, or more planes for color images. We model the signal being sampled (a sequence of pixel values forming a row, column, or time-varying sequence) as a random variable with a mean of zero. The probability distribution, shown in Figure 5.1, of pixel x1 given the value of pixel x0 has been shown empirically to be an exponential (laplacian) distribution [RY90]:
$$ P(X = {\mathbf{ }}\chi _1 {\mathbf{ }} - {\mathbf{ }}\chi _0 ) = {\mathbf{ }}\frac{{e^{ - \lambda |\chi _1 {\mathbf{ }} - {\mathbf{ }}\chi _0 |} }} {{2\lambda }} $$


Fast Fourier Transform Discrete Cosine Transform Discrete Fourier Transform Continuous Tone Image Fast Fourier Transform Coefficient 


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© Kluwer Academic Publishers 1997

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