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digital image processing

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This document discusses different types of error free compression techniques including variable-length coding, Huffman coding, and arithmetic coding. It then describes lossy compression techniques such as lossy predictive coding, delta modulation, and transform coding. Lossy compression allows for increased compression by compromising accuracy through the use of quantization. Transform coding performs four steps: decomposition, transformation, quantization, and coding to compress image data.

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S.Nandhini II-M Sc(CS&IT), Nadar Saraswathi College of Arts and Science, Theni.
ERROR FREE COMPRESSION  Error free compression is the only acceptable means of data reduction.  One such application is the archival of medical or business documents.  Need for error free compression is motivated by the intended use or nature of the images under consideration.
There types in error free compression  Variable-length coding  Huffman coding  Arithmetic coding  Variable-length coding  Error-free image compression is to reduce only coding redundancy.  coding redundancy normally is present in any natural binary encoding of the gray level in an image.
HUFFMAN CODING  Coding the symbol of an information source individually.  Huffman coding yields the smallest possible number of code symbols per sources symbol.  The constraint that the source symbol be coded one at a time.
digital image processing
ARITHMETIC CODING  Arithmetic coding generates non-block codes.  A one-to-one correspondence between source symbols and code words does not exist  Sequence of source symbols is assigned a single arithmetic code word.
digital image processing
LOSSY COMPRESSION  Lossy compression encoding is based on the concept of compromising the accuracy  The reconstructed image in exchange for increased compression.  The resulting distortion can be tolerated  The increase in compression can be significant.
LOSSY PREDICTIVE CODING  Add a quantizer to the model introduced examine the resulting trade-off between reconstruction accuracy and compression performance.  Lossy predictive coding model  A)encoder  B)decoder
ENCODER AND DECODER
DELTA MODULATION  Delta modulation(DM) is a simple but well-known form of lossy predictive coding in which the predictor and quantizer are defined
DELTA MODULATION
digital image processing
TRANSFORM CODING  Transform coding a reversible, linear transform is used to map the image into a set of transform coefficients.  Which are then quantized and coded.
TRANSFORM CODING
Performs four relatively straightforward operations  DECOMPOSITION  TRANSFORMATION  QUANTIZATION  CODING An NXN input of image first is subdivided into subimages of size nXn. Which are then transformed to generate(N/n)2 sub image transform arrays.
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digital image processing

  • 1. S.Nandhini II-M Sc(CS&IT), Nadar Saraswathi College of Arts and Science, Theni.
  • 2. ERROR FREE COMPRESSION  Error free compression is the only acceptable means of data reduction.  One such application is the archival of medical or business documents.  Need for error free compression is motivated by the intended use or nature of the images under consideration.
  • 3. There types in error free compression  Variable-length coding  Huffman coding  Arithmetic coding  Variable-length coding  Error-free image compression is to reduce only coding redundancy.  coding redundancy normally is present in any natural binary encoding of the gray level in an image.
  • 4. HUFFMAN CODING  Coding the symbol of an information source individually.  Huffman coding yields the smallest possible number of code symbols per sources symbol.  The constraint that the source symbol be coded one at a time.
  • 6. ARITHMETIC CODING  Arithmetic coding generates non-block codes.  A one-to-one correspondence between source symbols and code words does not exist  Sequence of source symbols is assigned a single arithmetic code word.
  • 8. LOSSY COMPRESSION  Lossy compression encoding is based on the concept of compromising the accuracy  The reconstructed image in exchange for increased compression.  The resulting distortion can be tolerated  The increase in compression can be significant.
  • 9. LOSSY PREDICTIVE CODING  Add a quantizer to the model introduced examine the resulting trade-off between reconstruction accuracy and compression performance.  Lossy predictive coding model  A)encoder  B)decoder
  • 11. DELTA MODULATION  Delta modulation(DM) is a simple but well-known form of lossy predictive coding in which the predictor and quantizer are defined
  • 14. TRANSFORM CODING  Transform coding a reversible, linear transform is used to map the image into a set of transform coefficients.  Which are then quantized and coded.
  • 16. Performs four relatively straightforward operations  DECOMPOSITION  TRANSFORMATION  QUANTIZATION  CODING An NXN input of image first is subdivided into subimages of size nXn. Which are then transformed to generate(N/n)2 sub image transform arrays.