Multi-Scale Image Edge Detection Based on Wavelet Transform

The MATLAB source code for multi-scale image edge detection based on wavelet transform represents a widely-used image processing algorithm. This algorithm employs wavelet transform to extract edge information from images and utilizes multi-scale analysis to obtain edge detection results at different scales. By implementing this algorithm using MATLAB programming language, efficient edge detection can be performed on images with relatively accurate results. The implementation typically involves key functions such as wavelet decomposition (using functions like wavedec2), edge magnitude calculation at multiple scales, and edge localization through modulus maxima detection. The multi-scale characteristics of wavelet transform enable this algorithm to capture detailed image information, thereby enhancing the precision and effectiveness of edge detection. The code generally includes steps for selecting appropriate wavelet filters (such as Daubechies or Symlets), performing multi-resolution analysis, and combining edge information across scales using fusion techniques. This approach allows for better noise immunity and improved detection of both coarse and fine edges in various image types. Therefore, the MATLAB source code for wavelet transform-based multi-scale image edge detection serves as a highly valuable tool that finds extensive applications in the field of image processing, particularly in medical imaging, remote sensing, and computer vision applications where accurate edge information is crucial for subsequent processing stages.