Image Matching using Wavelet Feature Extraction

An image matching MATLAB program utilizing wavelet feature extraction is an algorithm designed for image processing applications. The program begins by performing a 2D wavelet transformation on the input image using MATLAB functions like wavedec2(), which decomposes the image into frequency domain information. Subsequently, the algorithm extracts approximation coefficients (low-frequency components) that characterize the image's overall structural features. To enhance feature quality and reduce noise interference, the program eliminates coefficients with negligible impact on feature representation through thresholding techniques such as wthresh() or wdencmp(). This series of processing steps - transformation, selective coefficient extraction, and noise reduction - enables more accurate image matching results by focusing on robust feature descriptors. The MATLAB implementation provides both computational efficiency and visualization capabilities, facilitating better understanding and processing of image data for computer vision applications.