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. Project Overview. Purpose: create a software implementation of EZW coder for image compression Overall process flow-chart:. Step 1: 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

Embedded Image coding using zero-trees of Wavelet Transform

Authors: Harish Rajagopal

Brett Buehl


Project overview

Project Overview

  • Purpose: create a software implementation of EZW coder for image compression

  • Overall process flow-chart:


Step 1 wavelet transform

Step 1: Wavelet Transform

  • 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


Step 2 ezw coding

Step 2: EZW Coding

  • Flow-chart for EZW encoding:

(See next slide for more details)


Ezw coding cont d

EZW Coding Cont’d

  • The EZW consists of two algorithms:

1. Dominant Pass Flow-Chart

2. Subordinate Pass Flow-Chart


Step 3 arithmetic encoding

Step 3: Arithmetic Encoding

  • 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


Results

Results:

  • 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


Compression comparisons

Compression Comparisons:


Image demonstration

Image Demonstration:

Original Image

Reconstructed image

Difference Image

Initial DWT

Reconstructed DWT


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