Anti-halation method of visible and infrared image fusion based on improved IHS-Curvelet transform

Abstract

In order to solve the problem of driver halation caused by the abuse of high beam lights at night, the anti-halation method of visible and infrared image fusion was proposed based on improved Curvelet transform in IHS color space. The method could effectively express the two-dimensional detail information of the image by improving the Curvelet transform, and improved the image clarity. The proposed fusion strategy of self-adjusting low-frequency coefficient weights could remove the halation information and avoid its participation in the fusion process. The color information in the original image was preserved by combining with the IHS transform to avoid color distortion. Subjective and objective analysis of the experiment results show that the method can eliminate the halation more completely. Compared with IHS-wavelet fusion, standard deviation, average gradient, edge intensity and entropy of the fusion image increase by 47.15%, 53.10%, 52.46% and 4.45%, respectively, its contrast and clarity are significantly enhanced, the details are also more abundant, and the visual effect of the human eye is better. The method is helpful for the driver to observe the road condition ahead, make judgment in advance, eliminate safe hidden trouble and improve the safety of night driving.