Wavelet Transform-Based Image Compression

The MATLAB program for wavelet transform-based image compression is a specialized implementation that utilizes wavelet transform technology to compress digital images. Wavelet transform serves as a mathematical tool that decomposes images into wavelet coefficients at different frequency bands, enabling selective compression based on coefficient significance. This program allows users to perform efficient image compression within the MATLAB environment, optimizing storage requirements and enhancing image transmission efficiency. Through practical implementation, users can manipulate compression parameters such as threshold levels and decomposition layers to achieve varying compression ratios and quality outcomes, accommodating diverse application requirements. The core algorithm typically involves discrete wavelet transformation using functions like wavedec2 for 2D decomposition, coefficient thresholding with wthresh to eliminate insignificant coefficients, and image reconstruction using waverec2. Key parameters like wavelet type (e.g., Haar, Daubechies) and compression ratio can be adjusted through MATLAB's graphical interface or script configurations. Ultimately, this wavelet-based compression program provides robust solutions for image processing tasks, offering both convenience and flexibility in handling various compression scenarios.