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sizes is to normalize or weight each coefficient based on its visual importance. All of the normalized coefficients may then be quantized in the same manner, such as rounding to the nearest integer (uniform quantization). Normalization or weighting effectively scales the quantizer from one coefficient to another. The MPEG-2 video compression system utilizes perceptual weighting, wherein the different DCT coefficients are weighted according to a perceptual criterion prior to uniform quantization. Quantizer matrices determine the perceptual weighting. The compression system allows for modifying the quantizer matrices before each picture.



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Quantization creates an efficient, discrete representation for the data to be transmitted [10]. Code word assignment takes the quantized values and produces a digital bit stream for transmission. Hypothetically, the quantized values could be simply represented using uniform- or fixedlength code words. Under this approach, every quantized value would be represented with the same number of bits. As outlined previously in general terms, greater efficiency, in terms of bit rate, can be achieved with entropy coding. Entropy coding attempts to exploit the statistical properties of the signal to be encoded. A signal, whether it is a pixel value or a transform coefficient, has a certain amount of information, or entropy, based on the probability of the different possible values or events occurring. For example, an event that occurs infrequently conveys much more new information than one that occurs often. The fact that some events occur more frequently than others can be used to reduce the average bit rate. Huffman Coding. Huffman coding, which is utilized in the ATSC DTV video compression system, for example, is one of the most common entropy coding schemes [10]. In Huffman coding, a codebook is generated that can approach the minimum average description length (in bits) of events, given the probability distribution of all the events. Events that are more likely to occur are assigned shorter-length code words and those less likely to occur are assigned longer-length code words. Run Length Coding. In video compression, most of the transform coefficients frequently are quantized to zero [10]. There may be a few non-zero low-frequency coefficients and a sparse scattering of non-zero

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high-frequency coefficients, but most of the coefficients typically have been quantized to zero To exploit this phenomenon, the two-dimensional array of transform coefficients is reformatted and prioritized into a one-dimensional sequence through either a zigzag or alternate scanning process This results in most of the important non-zero coefficients (in terms of energy and visual perception) being grouped together early in the sequence They will be followed by long runs of coefficients that are quantized to zero These zero-value coefficients can be efficiently represented through run length encoding In run length encoding, the number (run) of consecutive zero coefficients before a non-zero coefficient is encoded, followed by the non-zero coefficient value The run length and the coefficient value can be entropy-coded, either separately or jointly The scanning separates most of the zero and the non-zero coefficients into groups, thereby enhancing the efficiency of the run length encoding process.

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Also, a special end-ofblock (EOB) marker is used to signify when all the remaining coefficients in the sequence are equal to zero This approach can be extremely efficient, yielding a significant degree of compression In the alternate- or zigzag-scan technique, the array of 64 DCT coefficients is arranged in a one-dimensional vector before run length/amplitude code word assignment Two different one-dimensional arrangements, or scan types, are allowed, generally referred to as zigzag scan (shown in Figure E11a) and alternate scan (shown in Figure E11b) The scan type is specified before coding each picture and is permitted to vary from picture to picture Channel Buffer Whenever entropy coding is employed, the bit rate produced by the encoder is variable and is a function of the video statistics [10].

Everyone loves Nachos! So why not take a bag, spread them in a bowl and cover with grated cheese. Then place the bowl in your solar cooker to melt the cheese and give you toasty hot nachos!

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