小波分析实验：二维离散小波变换Mallat算法深入理解与应用

The purpose of the experiment is to deepen the understanding of two-dimensional discrete wavelet transformation and Mallat fast algorithm through programming, and to enhance the rational and perceptual understanding of two-dimensional wavelet decomposition and reconstruction. It also aims to improve programming skills, laying the foundation for future learning and work. The experiment uses a computer and matlab6.51/1 as the tools. The appendix includes the two-dimensional wavelet decomposition function, which takes in the input of the two-dimensional image and the wavelet name, and outputs the multi-pole wavelet decomposition coefficient matrix. The function includes the low-pass and high-pass filters, and performs the row and column wavelet transformations. The experiment is aimed at enhancing the understanding and proficiency in utilizing the Mallat fast algorithm for two-dimensional discrete wavelet transformation. Overall, the experiment focuses on implementing the Mallat fast algorithm for two-dimensional discrete wavelet transformation. The experiment aims to deepen the understanding of the theoretical principles behind wavelet transformation and apply the Mallat fast algorithm through programming. The experiment is essential for enhancing the understanding of two-dimensional wavelet decomposition and reconstruction and improving programming skills. By implementing the Mallat fast algorithm, the experiment also aims to lay the foundation for future learning and work in the field of wavelet analysis and image processing. The experiment utilizes the computer and matlab6.51/1 as the main tools, and the appendix includes the two-dimensional wavelet decomposition function, which is crucial for the implementation of the Mallat fast algorithm. Overall, the experiment is significant for advancing knowledge and skills in the field of wavelet analysis and image processing.