MATLAB Implementation of Wavelet Zerotree Algorithm for Image Compression

This code provides a MATLAB implementation of the wavelet zerotree algorithm for image compression. The implementation features well-organized subroutines and includes complete source code for calculating the peak signal-to-noise ratio (PSNR) of compressed images to evaluate compression effectiveness.

The wavelet zerotree algorithm in this implementation effectively reduces image redundancy by exploiting the self-similarity across different wavelet scales. The core algorithm involves wavelet decomposition using functions like wavedec2(), followed by thresholding and zerotree encoding to eliminate insignificant coefficients. This approach enables efficient image compression while preserving important visual information.

The program allows users to easily compress images and quantitatively assess compression quality through PSNR calculation. Key functions include entropy coding implementation and bit-rate control mechanisms for optimized compression performance.

Additionally, the provided source code offers flexibility for customization and optimization according to specific requirements. By studying the implementation details, users can gain deeper insights into wavelet zerotree principles, including coefficient scanning methods and significance map encoding techniques.

This implementation serves as a practical resource for understanding and applying wavelet-based compression algorithms in digital image processing applications.