人眼视觉感知驱动的梯度域低照度图像对比度增强

摘要

Traditional contrast enhancement methods cannot simultaneously compress the dynamic range ,adjust the brightness and enhance or preserve the details of images on the low‐light images processing .Combining the human visual perception characteristics , a novel contrast enhancement method is proposed to enhance low‐light images via a global brightness mapping to local details compensation strategy .Firstly ,a nonlinear global brightness mapping model is employed to compress the dynamic range and adjust the overall brightness of the image .Then ,the image gradient filed is modified to enhance and restore the local details by combining the luminance masking and suprathreshold contrast perception characteristics of human visual system . Finally a new enhanced image is obtained by using a fast Poisson solver on the target gradient field .The results demonstrate that the proposed algorithm enhances both global and local contrast effectively and improves the visibility of the low‐light images .%针对传统的对比度增强方法在对低照度图像进行处理时不能同时顾及压缩动态范围、调整亮度以及增强或保持细节等问题，提出一种基于人眼视觉感知特性的、从全局亮度映射到局部细节补偿的低照度图像对比度增强方法。首先通过非线性全局亮度映射模型压缩图像的动态范围，提高图像的整体亮度水平；然后结合人眼视觉系统的亮度掩蔽特性和超阈值对比度感知特性，非线性地调整图像的局部梯度场增强和恢复图像的局部细节；最后在目标梯度场上通过快速求解泊松方程获取增强后的图像。实验结果表明，该方法能够有效地增强低照度图像的全局和局部对比度，提升了低照度图像的视见度。