Source Code for Gabor Algorithm Implementations in MATLAB and C

This article presents the source code implementations of the Gabor algorithm in both MATLAB and C programming languages. Let's explore this algorithm in depth. The Gabor filter is a linear filter extensively used in signal processing, image processing, and computer vision applications. Originally proposed by Dennis Gabor in the early 1940s, it was designed to characterize local time-frequency properties in optical images. The fundamental concept behind Gabor filters integrates a Gaussian window function with a sinusoidal wave, creating a specialized filter with specific frequency and orientation characteristics.

In practical implementation, Gabor filters typically involve creating a complex-valued function where the real component combines a Gaussian envelope with a cosine wave, while the imaginary part pairs the Gaussian with a sine wave. This dual-component approach enables simultaneous analysis of both magnitude and phase information. The mathematical formulation generally follows: G(x,y) = exp(-(x'²+y'²)/(2σ²)) × exp(2πjFx'), where x' and y' represent rotated coordinates to achieve orientation selectivity.

For MATLAB implementations, key functions include creating parameterized Gabor kernels using meshgrid for coordinate generation, implementing the Gaussian-modulated complex sinusoid, and applying convolution operations via imfilter or conv2 functions. The code typically involves adjusting critical parameters such as wavelength (λ), orientation (θ), phase offset (φ), and the standard deviation (σ) of the Gaussian envelope.

C implementations require manual matrix operations for kernel generation and custom convolution routines, often optimizing performance through precomputation and memory management techniques. The algorithm finds widespread application in image processing domains including texture analysis through filter bank responses, image enhancement via frequency-domain filtering, and feature extraction for pattern recognition systems.

Understanding how to implement Gabor algorithm source code in both MATLAB and C is crucial for researchers and developers working on advanced image and signal processing projects. This article provides comprehensive programming guidance to help you effectively apply Gabor filters for various computational tasks.