Lossless predictive coding in Digital Image Processing

Feb 7, 2016Download as PPTX, PDF8 likes17,496 views

Lossless predictive coding eliminates inter-pixel redundancies in images by predicting pixel values based on surrounding pixels and encoding only the differences between actual and predicted values, rather than decomposing images into bit planes. The coding system consists of identical encoders and decoders that each contain a predictor. The predictor generates an anticipated pixel value based on past inputs, the difference between actual and predicted values is variable-length encoded, and the decoder uses the differences to reconstruct the original image losslessly.

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).

 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.

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Lossless predictive coding in Digital Image Processing

1. LOSSLESS PREDICTIVE CODING

2. 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).

3. LOSSLESS CODING MODEL

4.  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

5.  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.

6. EXAMPLE

7. THANK YOU

Lossless predictive coding in Digital Image Processing

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