基于NF-ICM模型的图像增强算法
摘要
Utilizing the intersecting cortical model (ICM) to enhance degraded images under poor illumination is presented. As the key point, the general mapping function (MF) for image enhancement is deduced firstly on the basis of the nature-firing ICM (NF-ICM), which restrains the traditional autowave effect of blurring details and contrast. Then, the sigmoid MF is especially proposed to map the input gray-level to a more proper range for visual looking, and it solves over-enhancement and artifact by the classical logarithm one. For image enhancement application, the optimized parameters, initial threshold, and stopping condition in NF-ICM are all analyzed in detail. Simulation results prove that the proposed method has more contrasted, colorful, and good-visual performance.