MATLAB Source Code for Image Deblurring Processing

This is a MATLAB source code package for image deblurring processing, including sample source images. The implementation performs restoration based on classical image blurring models, specifically using non-blind restoration techniques where the blur kernel is known or estimated beforehand. Image deblurring processing is a technique used to enhance image clarity by eliminating blur effects, making images sharper and bringing out more detailed features. This source code provides a practical implementation that helps restore blurred images and includes sample images for reference and comparison. The code implementation likely includes key MATLAB functions such as: - Image convolution operations to model blurring effects - Deconvolution algorithms (possibly Wiener filter or Lucy-Richardson deconvolution) - Point Spread Function (PSF) handling for blur kernel representation - Noise reduction and regularization techniques to stabilize the restoration process Through using this source code, you can learn and understand the principles and methods of image deblurring processing, as well as how to implement these techniques in MATLAB. The implementation demonstrates practical approaches to handling common blur types like motion blur or Gaussian blur. In both academic research and practical image processing applications, image deblurring represents an important and fascinating field. This source code package serves as an educational resource and practical tool for those working with image enhancement technologies. We hope this resource proves valuable for your image processing projects and learning endeavors!