Illumination-Robust Face Preprocessing Algorithm Using Wavelet Transform and Homomorphic Filtering

This article presents an illumination-robust face preprocessing algorithm that employs wavelet transform and homomorphic filtering techniques. During the preprocessing stage, the algorithm effectively mitigates illumination variations' impact on facial recognition, thereby improving identification accuracy. The implementation typically involves: 1) Applying discrete wavelet transform (DWT) to decompose facial images into frequency subbands, 2) Using homomorphic filtering in the logarithmic domain to separate illumination and reflectance components, and 3) Reconstructing enhanced images through inverse wavelet transform. Key functions would include wavelet decomposition functions (like wavedec2 in MATLAB) and Butterworth-based homomorphic filters for frequency domain processing. The algorithm preserves essential facial features while enhancing image clarity, ultimately boosting the reliability and precision of face recognition technology across diverse practical applications.