Cohen-Daubechies-Feauveau 9-7 Wavelet Transforms with MATLAB Implementation

In this article, we explore the Cohen-Daubechies-Feauveau 9-7 wavelet transform algorithm, a widely utilized tool in digital signal processing. The core principle of this algorithm involves decomposing signals into different frequency components through forward transformation and reconstructing them via inverse transformation, enabling sophisticated signal manipulation. Using MATLAB programming language, we provide complete implementation code that demonstrates both the decomposition and reconstruction processes. The implementation includes key components such as lifting scheme operations, filter coefficient handling, and multi-level decomposition structure. This algorithm finds significant applications in signal compression, image processing, and audio processing domains, serving as an essential component in modern digital signal processing systems. The MATLAB code showcases practical implementation aspects including boundary handling, filter bank design, and perfect reconstruction properties characteristic of this biorthogonal wavelet family.