为提高低亮度红外与可见光图像融合的视觉效果，提出了一种对比度增强的图像融合算法。使用双边滤波器对光照进行估计，提出了双边滤波子带分解多尺度Retinex变换，并在此基础上对原图像进行子带分解。使用基于局部空间频率的细节增强融合策略完成子带内系数融合，使用全局方差加权融合策略完成子带间系数融合。使用非线性拉伸法将融合结果由对数域映射到显示域。实验结果表明，该方法可有效消除光晕，提高融合图像清晰度，使细节信息更突出。

A contrast enhanced image fusion algorithm is proposed to improve the visual effect of fused image from infrared and visible images at low lightness. Estimating background luminance by bilateral filter, the subband-decomposed multiscale Retinex with bilateral filtering is proposed, and original images are decomposed using proposed transformation. Coefficient matrixes in the same subband are fused by using detail enhancement strategy based on local space frequency, and fused coefficient matrixes in different subbands are fused by global variance weighted sum. The fusion result is needed for the transition from the logarithmic domain to the display domain by improved nonlinear stretching. The results of experiments demonstrate that the proposed algorithm can effectively overcome the halo phenomenon, improving definition of fused image, and the detail information is more salient.