Gaussian High-Pass Filter for Image Processing with MATLAB Implementation

This article presents a MATLAB-implemented Gaussian high-pass filter source code designed for effective image processing. The code demonstrates clear algorithmic logic, straightforward execution, and practical adaptability. In digital image processing, Gaussian high-pass filters excel at enhancing edge features and detail information by suppressing low-frequency components while preserving high-frequency elements. Key implementation aspects include: - Frequency-domain filtering using Fourier transform operations - Gaussian transfer function construction with controllable cutoff frequency - Parameter customization for sigma (standard deviation) to adjust filter bandwidth - Inverse Fourier transform for spatial domain image reconstruction The filter effectively sharpens image edges and accentuates fine details through frequency attenuation characteristics, thereby improving overall image quality. Users can modify critical parameters like cutoff frequency and kernel size to accommodate various image processing requirements. This implementation provides a foundational framework for edge detection, image sharpening, and detail enhancement applications. <p>The provided MATLAB source code enables immediate experimentation with Gaussian high-pass filtering techniques. Its modular structure allows seamless integration into larger image processing pipelines while maintaining computational efficiency through optimized matrix operations. The code includes commented sections explaining frequency domain conversion steps and Gaussian kernel generation methodology. Adjust the sigma parameter to control the degree of high-frequency emphasis - larger values produce smoother transitions while smaller values create more aggressive edge enhancement. This implementation serves as both an educational tool for understanding frequency-domain filtering concepts and a practical solution for real-world image enhancement tasks.</p>