为客观、准确、便捷地评价目标的伪装效果，利用人眼视觉注意机制建立了伪装效果评价模型. 提取输入图像的亮度和朝向特征，融合色差分布图，得到相应的特征显著图. 根据竞争机制和禁止返回机制，计算出注意焦点. 基于BP神经网络建立了视觉焦点转移特性与目标发现概率的对应关系模型，从而准确地量化目标伪装效果.实验中选用44幅南方林地型图像进行BP神经网络训练和有效性检验，结果表明，该模型能够有效评价目标的伪装效果，并具有可操作性强、量化准确的优点.

 In order to evaluate target camouflage effectiveness objectively, precisely and conveniently, we establish a model based on the human visual attention mechanism. A conspicuity map is obtained based on intensity of the input image, orientation characteristics and chromatic aberration. Shift of the focus of attention (FOA) is selected and measured with the mechanisms of winner-take-all (WTA) and inhibition of return. The relation between the FOA shift and target detection probability is obtained using a BP neural network. Target camouflage effectiveness can be measured precisely. Experiments are performed on 44 images of southern forest for training the BP neural network and validating the model. The results show that this
model has advantages in precision, determinability and operability.