Research on Image Compression Coding Based on Wavelet Transform

The MATLAB implementation of EZW (Embedded Zerotree Wavelet) provides an image compression coding method based on wavelet transform. This approach performs wavelet decomposition on images to convert them into frequency domain representations, then encodes and compresses the image according to different frequency components. The wavelet transform effectively extracts local image features and represents them as frequency components at various scales and orientations. The EZW algorithm, implemented through MATLAB's wavelet toolbox functions like wavedec2 for 2D decomposition, is an image compression coding technique that progressively approximates the original image through successive refinement. The coding process involves zerotree quantization and entropy coding to achieve lossy compression, significantly reducing storage requirements and transmission bandwidth. Key implementation aspects include threshold selection using wthresh function and hierarchical encoding of wavelet coefficients. Therefore, this MATLAB EZW program can be utilized for image compression coding, enabling efficient storage and transmission of image data through optimized bit allocation across different frequency bands.