MATLAB Wavelet-Based Image Compression Implementation

In this document, I would like to share a MATLAB-based wavelet image compression program. Developed in 2008, this implementation utilizes wavelet transform technology to achieve efficient image compression. The program demonstrates excellent performance and is suitable for various experimental purposes. Through this implementation, you can explore the principles and practical applications of wavelet-based image compression. The code employs key wavelet transform functions such as dwt2() for decomposition and idwt2() for reconstruction, along with thresholding techniques for coefficient quantization. The algorithm typically involves multi-level wavelet decomposition, coefficient thresholding to eliminate insignificant details, and entropy coding for final compression. This program serves as an educational tool to help you understand relevant technologies and algorithms in the image processing domain. By experimenting with this code, you can deepen your knowledge of image compression techniques and achieve better results in your research or experimental work. The implementation includes configurable parameters for wavelet types (Haar, Daubechies, etc.), compression ratios, and threshold values to facilitate comprehensive testing and analysis.