LOSSLESS PREDICTIVE CODING
LOSSLESS PREDICTIVE CODING  Does not require decomposition of an image into a collection of bit planes.  Based on eliminating the inter-pixel redundancies closely spaced pixels by extracting and code only the new information in each pixel. - New information: the difference between the actual and predicted value of that pixel.  The coding system consists of an encoder and a decoder, each contains an identical predictor (Fig. 8.19).
LOSSLESS CODING MODEL
 The predictor generates the anticipated value of that pixel based on some number of past inputs.  Form the difference or predictor en, which is coded using a variable-length code to generate the next element of the compressed data stream.  Generate fn based on global, local and adaptive
 In 1D linear prediction f(x , y) is a function of the previous pixels on the current line alone.  In 2D predictive coding, the prediction is a function of the previous pixel in a left -to-right, top-to-bottom scan of an image.  In 3D case, it is based on the pixels and the previous pixels of preceding frames.
EXAMPLE
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Lossless predictive coding in Digital Image Processing

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    LOSSLESS PREDICTIVE CODING Does not require decomposition of an image into a collection of bit planes.  Based on eliminating the inter-pixel redundancies closely spaced pixels by extracting and code only the new information in each pixel. - New information: the difference between the actual and predicted value of that pixel.  The coding system consists of an encoder and a decoder, each contains an identical predictor (Fig. 8.19).
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     The predictorgenerates the anticipated value of that pixel based on some number of past inputs.  Form the difference or predictor en, which is coded using a variable-length code to generate the next element of the compressed data stream.  Generate fn based on global, local and adaptive
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     In 1Dlinear prediction f(x , y) is a function of the previous pixels on the current line alone.  In 2D predictive coding, the prediction is a function of the previous pixel in a left -to-right, top-to-bottom scan of an image.  In 3D case, it is based on the pixels and the previous pixels of preceding frames.
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