Gaussian Blur Source Code for Image Blind Restoration

This Gaussian blur source code provides a comprehensive implementation that is particularly valuable for researchers specializing in image blind restoration. The code demonstrates the complete Gaussian blur algorithm implementation, including kernel generation using the Gaussian function and convolution operations with proper boundary handling. For blind restoration applications, the code illustrates how Gaussian blur can be modeled as a point spread function (PSF) and integrated into restoration algorithms. Key functions include sigma parameter configuration for controlling blur intensity, kernel size optimization, and efficient convolution implementation using separable filters for performance optimization. By studying this source code, researchers can gain deeper insights into Gaussian blur principles, understand its role in image degradation models, and develop practical skills for implementing blind restoration techniques that effectively reverse Gaussian-type blurring effects. This resource aims to support academic learning and research advancement in computational photography and image processing domains.