目前的大多数基于小波变换的图像融合算法，由于并没有细致考虑人眼的视觉特性，因而得到的融合效果有时并不理想。为了提高图像的融合效果，提出了一种新的基于人类视觉系统(HVS)的小波图像融合新算法。该算法充分考虑了人类视觉系统的特点，首先在多尺度小波分解的基础上，计算出每层每个像素邻域的纹理和边缘亮度相关量；然后自适应地求得加权融合系数；最后采用多层次迭代法来产生融合图像。实验结果表明，该算法不仅能使图像融合结果有较大的改善，而且有利于人眼对目标的探测和识别。

Most of current algorithms of image fusion are based on wavelet transform and the visual characteristics of eyes of human being are not sufficiently taken into account, thus failing to get perfect fusion effect in some circumstances. In this paper, we propose a new wavelet image fusion algorithm based on human visual system. In our algorithm we fully considers the characteristics of human visual system and calculate the relative terms of neighbor region's texture and edge luminance of each pixel at each level to adaptively acquire the weighted fusing coefficients. By using the method of multi|level iterative fusion, improved fused images are thus generated. Experiments show that our algorithm can achieve quite better fusion effect and is advantageous for human eye to detect and recognize targets.