Image Processing Based on Wavelet Transform

This article presents nearly 10 wavelet transform-based image processing programs implemented in MATLAB. These programs provide robust tools for various image processing tasks to enhance image quality and extract meaningful features. Through these implementations, users can perform critical operations including image denoising using thresholding techniques, multi-scale edge detection through wavelet coefficient analysis, and contrast enhancement via wavelet coefficient manipulation. Key functions utilized include wavedec2 for 2D wavelet decomposition, waverec2 for reconstruction, and wthresh for thresholding operations. The algorithms leverage wavelet transform's multi-resolution analysis capabilities to preserve important image details while effectively removing noise. Whether you're beginning your journey in image processing or are an experienced professional, these ready-to-use M-file programs offer efficient and practical solutions that can significantly streamline your workflow and expand the possibilities in your image processing projects.