针对人类视觉系统的双波段红外图像融合算法研究

Study of Dual-band Infrared Image Fusion Algorithm for Human Visual Systems

提出了一种针对人类视觉系统的双波段红外图像融合算法。首先采用非下采样Contourlet变换把源图像分解成尺多度、多方向上的子带,然后采用绝对值最大算子的方法对高频部分进行融合,采用基于区域方差的方法对低频部分进行融合,最后进行重构得到融合图像。对试验中采集的双波段红外图像进行了融合实验,并将融合效果与梯度金字塔变换方法和小波变换方法进行了比较。实验结果表明,针对人类视觉系统的双波段红外图像融合算法有效可行,可以获得比常用的算法更好的融合效果。

A dual-band infrared image fusion algorithm for human visual systems is put forward. First, the source images are decomposed into the multi-scale and multidirectional subbands by using a nonsubsampled contourlet transform method. Then, the highpass subband is fused by selecting the maximum absolute operator and the lowpass subbands is fused by using a method based on region variance. Finally, the fused image is obtained through image reconfiguration. A fusion experiment is made on the dual-band infrared images collected. The method is compared with the gradient pyramid transform and the wavelet transform in fusion effectiveness. The experimental result shows that this dual-band infrared image fusion algorithm for human visual systems is effective and feasible. It can obtain better fusion effectiveness than the common algorithms.