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Wavelets Processor

Bag om Wavelets Processor

The digital design of signal processing system has found its effectiveness in implementing systems that have many real-time computational requirements. In these systems, circuit design is of special interest to designers for implementing applications on commercially available off the shelf digital signal processors (DSPs) , field programmable gate array (FPGA) and application specific integrated circuits (ASIC). Image compression has been performed using Wavelet Transform as the tool. A new, better and much faster approach has been taken to Wavelet Transform multidimensional signals, called the Fast Lifting Wavelet Transform. Fast Lifting wavelet Transform Filter reduces the complexity by almost half and it allows rounding off to be performed on the filtered outputs and intermediate results and still achieving perfect reconstruction.We also compared our results with those reported by other researchers in the recent past and found them to be comparable and in certain cases even better.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9783845403571
  • Indbinding:
  • Paperback
  • Sideantal:
  • 72
  • Udgivet:
  • 12. juli 2011
  • Størrelse:
  • 234x174x5 mm.
  • Vægt:
  • 128 g.
  • BLACK NOVEMBER
Leveringstid: 2-3 uger
Forventet levering: 25. november 2024

Beskrivelse af Wavelets Processor

The digital design of signal processing system has found its effectiveness in implementing systems that have many real-time computational requirements. In these systems, circuit design is of special interest to designers for implementing applications on commercially available off the shelf digital signal processors (DSPs) , field programmable gate array (FPGA) and application specific integrated circuits (ASIC). Image compression has been performed using Wavelet Transform as the tool. A new, better and much faster approach has been taken to Wavelet Transform multidimensional signals, called the Fast Lifting Wavelet Transform. Fast Lifting wavelet Transform Filter reduces the complexity by almost half and it allows rounding off to be performed on the filtered outputs and intermediate results and still achieving perfect reconstruction.We also compared our results with those reported by other researchers in the recent past and found them to be comparable and in certain cases even better.

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