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TTM4142 Networked Multimedia Systems Video Basics Lossy Compression

TTM4142 Networked Multimedia Systems Video Basics Lossy Compression. Leif Arne Rønningen Autumn 2008. Distortion Measures. Quantization. Discrete Cosine Transform - DCT. Wavelet-based Coding.

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TTM4142 Networked Multimedia Systems Video Basics Lossy Compression

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  1. TTM4142 Networked Multimedia SystemsVideo BasicsLossy Compression Leif Arne Rønningen Autumn 2008

  2. Distortion Measures

  3. Quantization

  4. Discrete Cosine Transform - DCT

  5. Wavelet-based Coding • Fourier transform results in very fine resolution in the frequency domain, but gives no temporal resolution • Wavelet transform represents a signal with good resolution in both time and frequency

  6. The Discrete Haar Wavelet Transform • DWT • Multiresolution analysis Decompose the sequence for compression purposes, into components easier to handle. i – index pixel n – level of ’pyramid’

  7. Haar DWT Replace with pairwise average and difference small values Since every other element is used, has the same length as

  8. Inverse Haar DWT

  9. Example, 2D Haar DWT

  10. Example, con’t Intermediateoutput • 1D Haar DWT on rows givs • Then 1D Haar DWT on columns

  11. Example con’t, Output from 2D Haar DWT andGraphical Illustration

  12. Continuous Wavelet Transform - CWT Decompose a signal f(t) in time into frequency and time domains simultaneously mother wavelet

  13. CWT, example of mother wavelet shift scale

  14. Discrete Wavelet Transform - DWT • Multiresolution Analyses = the connection between wavelets in continuous time and filter banks in discrete time. Provides the tool to adapt signal resolution to only relevant details. • Scaling function determines average info • Wavelets (translates of scaling functions) determine detailed info where

  15. Low pass High pass

  16. mathematically,

  17. 2D DWT

  18. 2D Inverse DWT

  19. Example 8.8, see p235 in textbook

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