Wavelet Coefficient Extraction and Zerotree Encoding for Image Compression

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Resource Overview

Implementation of HAAR wavelet transforms for wavelet coefficient relationship extraction, followed by zerotree encoding for compression and subsequent decompression to reconstruct the original image. Contains minor optimizations that serve as valuable references for similar implementations.

Detailed Documentation

Based on the user's requirements, we utilize HAAR wavelet transforms to extract relationships between wavelet coefficients and apply zerotree encoding for compression. The decompression process reconstructs the original image from compressed data. The implementation involves key steps: performing 2D HAAR wavelet decomposition using discrete wavelet transform functions (e.g., wavedec2 in MATLAB), analyzing coefficient relationships across decomposition levels, and implementing zerotree encoding algorithms like EZW or SPIHT that exploit parent-child dependencies in wavelet trees. Additionally, I've incorporated minor optimizations including threshold adjustment for coefficient quantization and efficient bit-plane coding techniques, which demonstrate practical approaches worth referencing for similar compression projects.

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