MATLAB Implementation of Homomorphic Filtering

Homomorphic filtering is a highly effective image processing technique that operates by compressing the dynamic range of an image while simultaneously enhancing its contrast. This method finds extensive applications across various domains including medical imaging, computer vision, and image enhancement. In MATLAB implementation, homomorphic filtering typically involves several key steps: first converting the image to logarithmic domain to separate illumination and reflectance components, then applying Fourier transform to work in frequency domain. The algorithm utilizes specialized filter functions (such as Gaussian high-pass filters) to attenuate low-frequency illumination variations while preserving high-frequency reflectance details. After frequency domain processing, inverse Fourier transform and exponential operations are applied to reconstruct the enhanced image. By adjusting brightness and contrast characteristics, homomorphic filtering makes image details more clearly visible, thereby significantly improving image quality and readability. The technique proves particularly valuable for images with uneven illumination or poor contrast conditions, making it a practical and powerful solution in digital image processing.