GABOR Filter Design

This resource provides GABOR filter design implementations through two MATLAB-based programs. The GABOR filter design process begins with determining critical parameters including center frequency and bandwidth specifications. Based on specific application requirements, appropriate GABOR filter parameters can be selected through MATLAB's signal processing toolbox. The implementation involves using MATLAB's built-in functions for filter optimization to achieve optimal filtering performance. Key steps include parameter initialization using gaborFilterBank function, frequency domain transformation via fft2, and convolution operations with imfilter for image processing applications. After design completion, the filters can be applied to various image processing tasks such as texture analysis using gray-level co-occurrence matrices and edge detection through gradient-based methods. These MATLAB implementations provide convenient tools for designing and applying GABOR filters, supporting diverse image processing requirements through configurable parameter settings and optimized computational algorithms.