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Embedded Image coding using zero-trees of Wavelet TransformPowerPoint Presentation

Embedded Image coding using zero-trees of Wavelet Transform

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Embedded Image coding using zero-trees of Wavelet Transform

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Embedded Image coding using zero-trees of Wavelet Transform

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Embedded Image coding using zero-trees of Wavelet Transform

Authors: Harish Rajagopal

Brett Buehl

- Purpose: create a software implementation of EZW coder for image compression
- Overall process flow-chart:

- Step 1a: Replace each image row with its 1D DWT
- Step 1b: Replace each image column with its 1D DWT
- Step 1c: Repeat steps (1) and (2) on the lowest subband to create the next scale
- Step 1d: Repeat step (3) until the desired number of scales has been created

Original Image

Discrete Wavelet Transform

- Flow-chart for EZW encoding:

(See next slide for more details)

- The EZW consists of two algorithms:

1. Dominant Pass Flow-Chart

2. Subordinate Pass Flow-Chart

- Uses symbol probabilities for lossless compression
- Added to EZW implementation to increase compression
- Encodes output from EZW encoder
- P,N,T,Z,E or 0,1,E

Symbol Probabilities & subintervals

Process of encoding a1a2a3a4

- Compression ratios similar to JPEG image compression
- Demonstration image results:
- cameraman.bmp – 16.8:1 compression ratio
- lena.bmp – 7.5:1 compression ratio
- barbara.bmp – 7.5:1 compression ratio

Original Image

Reconstructed image

Difference Image

Initial DWT

Reconstructed DWT