为实现面向具体视觉任务提出的融合图像“目标探测感知质量”的客观度量，通过分割红外源图像中感兴趣区域确定融合图像中人眼敏感的目标和背景区域，结合主观评价实验观察条件与人类视觉系统特性确定目标邻域面积，利用人类视觉系统空间积分特性确定目标区域人眼敏感权重，利用人类视觉系统亮度掩盖特性确定多目标权重，构建了基于目标邻域对比度的客观评价模型。和基于韦伯定律的目标与背景对比度客观评价模型相比，目标邻域对比度客观评价模型在与主观评价结果的准确性、一致性和单调性方面均有显著提高，这对实际应用的图像融合系统具有现实意义。

To realize the objective measure of the “target detection perceptual quality” index which is proposed for specific visual tasks, a new fusion image target detection objective assessment model is provided based on target neighborhood contrast. In the model design procedure, the eye-sensitive target and background regions are acquired by the segmentation of region of interested with the help of infrared images. Meanwhile, the target neighborhood area is acquired by the analysis on human visual system characteristics and the observing condition of the subjective assessment experiment. Furthermore, the eye-sensitive weight is acquired based on human visual system dimensional integral characteristics. Finally, the multi-target weight is acquired by the human visual system luminance masking effect. Compared to target and background contrast model based on Weber law, the method is better prominently at the accuracy, consistency and monotonicity which has the realistic significance to the practical image fusion system.