Enhanced Gabor Filter Implementation Function

This enhanced Gabor filter implementation function differs from commonly available online versions by providing superior filtering performance and more effective image feature extraction. Gabor filters are frequency-domain based filters widely applied in image processing and computer vision applications. The implementation employs adjustable Gabor kernel functions with varying frequencies and orientations to efficiently extract texture and edge characteristics from images. Key implementation aspects include: - Customizable parameter tuning for frequency bandwidth and orientation selection - Optimized convolution operations using separable kernel properties where applicable - Efficient spatial domain implementation with proper windowing functions - Multi-scale and multi-orientation filter bank configuration support Compared to standard downloadable filters, this implementation demonstrates higher computational efficiency and produces more discriminative features for pattern recognition tasks. The function allows for specific adjustments and optimizations based on image characteristics and application requirements to achieve optimal filtering results. For researchers and developers working on image feature extraction or computer vision applications, this Gabor filter implementation is highly recommended due to its robust performance and adaptability to various image processing scenarios. The code structure includes clear parameter interfaces and supports both real and imaginary component outputs for comprehensive feature analysis.