可见光与红外图像分区融合的夜视抗晕光方法

Night Vision Anti-halation Method Based on Partition Fusion of Visible and Infrared Images

针对夜视晕光图像区域特征差异大,导致融合图像视觉效果不理想的问题,提出一种可见光与红外图像分区融合的夜视抗晕光方法。先采用自适应阈值迭代法确定低频系数的晕光阈值,将低频系数划分为晕光与非晕光区域,在晕光区域采用非线性红外系数权值调节策略,依据图像晕光程度合理消除晕光;在非晕光区域采用灰度均值先验权值调节策略,提高较亮图像参与融合的权值,增强暗处区域的可见度。实验结果表明,本文方法对不同程度的夜视晕光场景均具有良好的适用性,能合理且有效地消除晕光,提高夜视融合图像的质量。

The imperfect visual effects in fused images are caused by the large difference between the regional features of night-vision halation images.To address this problem,a partition fusion method for visible and infrared images is proposed.First,the halation threshold of the low-frequency coefficient,determined by the adaptive threshold iteration method,divided the low-frequency coefficient into halation and nonhalation regions.In the halation region,the proposed nonlinear adjustment method for the infrared coefficient weights eliminated halation according to the degree of halation in the image.In the nonhalation region,the weight adjustment method based on the prior grayscale mean was applied to improve the weight of brighter images participating in the fusion to enhance the visibility of dark areas.The experimental results show that the proposed method can be applied to night-vision halation scenes of different degrees to eliminate halation and improve the quality of night-vision image fusion.