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Burrows Wheeler Transform In Image Compression

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Presentation on theme: "Burrows Wheeler Transform In Image Compression"— Presentation transcript:

1 Burrows Wheeler Transform In Image Compression
Markus Gärtner David Havelin Classroom Presentation 1st December 2000

2 Overview Project Goals Burrows Wheeler Transform (BWT)
Application of the BWT: Lossless Compression Lossy Compression Performance Conclusion Markus Gärtner, David Havelin: Burrows Wheeler Transform Stanford University, 1st December 2000

3 Project Goals Implementation of an efficient Burrows-Wheeler Transform (BWT) algorithm Implementation of coding scheme for transformed data Analysis of lossless compression performance Possible combinations of BWT with Subband Coding schemes Markus Gärtner, David Havelin: Burrows Wheeler Transform Stanford University, 1st December 2000

4 Burrows-Wheeler Transform
Lossless Reversible Block-Sorting Algorithm Input: ABDACA 1 A B D C 2 3 4 5 6 Output: CADAAB I=2 Markus Gärtner, David Havelin: Burrows Wheeler Transform Stanford University, 1st December 2000

5 Lossless Compression BWT Move-to Front Entropy 1D Image Original MTF MTF/BWT JPEG-LS Peppers 7.5925 6.9449 5.5727 4.513 Lena 7.4451 6.6973 5.4819 4.237 Bridge 5.7056 5.1756 4.7974 5.500 Markus Gärtner, David Havelin: Burrows Wheeler Transform Stanford University, 1st December 2000

6 Subband Coding Wavelet Transform Q Run- length BWT MTF Entropy
Wavelet-BWT 1D DCT Q Run- length BWT MTF Entropy DCT-BWT Markus Gärtner, David Havelin: Burrows Wheeler Transform Stanford University, 1st December 2000

7 PSNR vs. Rate for image “peppers.tif”
Subband Coding - DCT PSNR vs. Rate for image “peppers.tif” JPEG quantization Markus Gärtner, David Havelin: Burrows Wheeler Transform Stanford University, 1st December 2000

8 Subband Coding - Wavelets
PSNR vs. Rate for image “peppers.tif” Markus Gärtner, David Havelin: Burrows Wheeler Transform Stanford University, 1st December 2000

9 Conclusions Image compression with BWT possible Limitations
Lack of scalability Performance of Said-Pearlman hard to reach Possibilities for improvement Sophisticated scanning techniques (Peano) Run-length Encoder Optimized Quantization Markus Gärtner, David Havelin: Burrows Wheeler Transform Stanford University, 1st December 2000


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