JPEG2000 Image Compression Implementation using MATLAB

This project implements JPEG2000 image compression using MATLAB programming language. The core algorithm utilizes Discrete Wavelet Transform (DWT), which converts images into frequency domain representations to reduce data redundancy. The implementation involves: 1. Image preprocessing and loading through MATLAB's imread() function 2. Multi-level DWT decomposition using wavelet filters (e.g., Daubechies wavelets) 3. Coefficient quantization and entropy coding stages 4. Compression ratio control through bit allocation strategies Key MATLAB functions employed include: - wavedec2() for 2D discrete wavelet decomposition - wcodemat() for coefficient quantization - entropy encoding functions for efficient data representation By modifying the image file path in the code configuration section, users can execute the program to visualize compression effects on different images. This project serves as an excellent learning resource for understanding image compression algorithms and practical MATLAB programming applications in digital signal processing. The implementation demonstrates proper handling of wavelet transform levels, quantization parameters, and rate-distortion optimization techniques characteristic of JPEG2000 standard.