Image Wavelet Decomposition Using Haar Wavelet Implementation in MATLAB

This program implements image wavelet decomposition using Haar wavelet in MATLAB. Image wavelet decomposition is a fundamental image processing technique that decomposes an image into different frequency subbands to extract detailed features. In this implementation, we utilize Haar wavelet as the decomposition basis function due to its computational simplicity and excellent compression properties. The algorithm performs both horizontal and vertical filtering operations using Haar wavelet filters (low-pass and high-pass) to generate approximation coefficients (LL), horizontal details (LH), vertical details (HL), and diagonal details (HH) subbands. Through wavelet decomposition, we obtain low-frequency components representing the image's main structure and high-frequency components capturing fine details, enabling applications like image compression and denoising. The implementation includes proper boundary handling and supports multi-level decomposition for enhanced analysis. Key functions involved may include wavedec2 for 2D wavelet decomposition and appcoef2/detcoef2 for coefficient extraction. We hope this program proves valuable for your image processing projects.