Homomorphic Filtering Algorithm for Image Processing

This presents a homomorphic filtering algorithm designed for image processing, which enhances image quality and visual effects through frequency domain operations. Homomorphic filtering is a frequency-domain image processing technique that adjusts image luminance and contrast parameters, resulting in clearer and more observable images. The algorithm operates by first applying a logarithmic transformation to separate illumination and reflectance components, followed by frequency domain filtering using transfer functions like Butterworth or Gaussian filters. Key implementation steps include: converting the image to logarithmic domain, applying Fourier transform, designing appropriate filter functions in frequency domain, and performing inverse transformations. Using homomorphic filtering algorithm, image details and features can be enhanced while preserving the overall structure and information content. By comparing images before and after filtering, practitioners can better understand the effectiveness and advantages of homomorphic filtering algorithms, particularly in handling multiplicative noise and improving images with uneven illumination.