基于改进交叉视觉皮质模型的彩色图像增强

摘要

为了获得更加符合人眼生理视觉感知的图像,提出了一种在HIS空间上的基于改进的交叉视觉皮质模型(ICM)的彩色图像增强算法.在分析传统ICM工作机制的基础上,保留原模型的基本特性,对模型中的内部活动项和动态阈值部分进行改进,将线性衰减变为非线性,满足了人眼对亮度感知的非线性；同时将衰减因子变为步长的减法,降低了算法复杂度并增强了算法的自适应性.结合图像增强的原理,对亮度分量采用符合视觉属性的阈值强度函数,同时对饱和度分量进行非线性处理.实验表明用该算法能获得更加清晰、鲜艳生动的处理结果.%To meet the physiological perception of human eyes, a color image enhancement algorithm based on improved Intersecting Cortical Model (ICM) was proposed. The internal activities and dynamic threshold were improved to nonlinear attenuation, which satisfied the nonlinear perception of human eyes. And the decay factor was replaced by the step factor, while maintaining some of the significant features of the original model. It applied the Threshold Versus Intensity (TVI) function of the human visual system on the intensity component of the input image to adjust the dynamic range compression. At the same time, it also adjusted the saturation component of the input image by nonlinearity. Compared to the original ICM, this algorithm reduced the complexity and improved the adaptability. The experimental results confirm that the method can obtain clear and bright results.