Implementation of Second-Order Gaussian Low-Pass Filter

This code implements a second-order Gaussian low-pass filter for image processing applications. The filter effectively reduces high-frequency noise in images, resulting in smoother and clearer output. The implementation employs MATLAB with the following technical workflow: First, critical filter parameters including kernel size and standard deviation are defined to control the filter's spatial characteristics. Then, a 2D Gaussian kernel is generated using these parameters through mathematical calculations based on the Gaussian distribution formula. Next, the convolution operation is performed between the created filter kernel and the input image using MATLAB's built-in functions, applying the filtering effect across the entire image. Finally, the processed image is output for subsequent analysis or further processing. This implementation demonstrates a practical approach to image quality enhancement through frequency-domain filtering, where the Gaussian kernel's sigma parameter directly controls the degree of smoothing applied to the image.