Image enhancement is a preprocessing technique to improve the visibility and highlight the features and details of the image for pattern recognition under varying lighting conditions. Three nonlinear image enhancement algorithms – LDNE (luma-dependent nonlinear enhancement), INDANE (integrated neighborhood dependent algorithm for nonlinear enhancement) and AINDANE (adaptive INDANE, which was implemented based on the statistical features of the image, such as histogram distribution, standard deviation, and frequency domain information.) – based on the principle of sensory attributes of the human visual cortex, are being developed in the ODU Vision Lab. It is observed that LDNE, INDANE and AINDANE algorithms provide extremely optimal results for preprocessing images so that the face regions in an image captured under extremely low or non-uniform lighting conditions are brightened and made more distinct.