DTCWT域的红外与可见光图像融合算法

针对红外与可见光图像融合存在融合图像对比度和清晰度降低、噪声干扰等问题，提出一种DTCWT域的红外与可见光图像融合算法。首先对源图像进行预增强处理；然后通过DTCWT正变换得到低频子带图像和高频子带图像；再分别利用基于直觉模糊集的融合规则融合低频子带图像，基于信息反差对比度的融合规则融合高频子带图像；最后对融合后的低频子带图像和高频子带图像进行DTCWT逆变换得到融合图像。实验结果表明，本文算法能有效提高融合图像对比度和清晰度，降低噪声干扰，客观评价指标总体优于现有算法的，运行效率也有所提升。

Fusion algorithm of infrared and visible images in DTCWT domain

Aiming at the problem that fusing infrared and visible images has low construct and clarity and high noise interference, a fusion algorithm of infrared and visible images in DTCWT domain is proposed. Firstly, the source image is pre-enhanced, then the low-frequency and high-frequency subband images are obtained by DTCWT positive transformation. Secondly, the low-frequency fusion rules based on intuitionistic fuzzy sets and the high-frequency fusion rules based on differential contrast of information are fused respectively. Finally, the fused image is obtained by DTCWT inverse transform of the low-frequency and high-frequency subbands. The experimental results show that the proposed algorithm can effectively improve the contrast and clarity of the fused image and reduce the noise interference, it has better objective evaluation index than the existing algorithms, and the operation efficiency is also improved.