本文从感知特征图与立体图像质量的关系出发, 提出了一种立体图像感知特征图失真程度预测立体图像质量的评价模型。首先, 从人类视觉系统对图像的理解方式出发, 提取立体图像的视觉感知特性相关的特征图像；然后, 计算感知特征图的失真程度, 构成感知特征集并作为立体图像的特征参数；最后, 用随机森林分类算法进行特征融合, 建立立体图像质量评价模型。实验结果表明, 本文模型符合人眼视觉特性, 能够较好地预测立体图像质量。

The contact between distortion of visual perception characteristics and quality of stereo image is explored, and a new stereo image quality assessment model is proposed in combination with visual perception characteristics and random forest learning method. Firstly, according to human visual system, a series of visual perception characteristics are extracted as features to measure the degree of distortion stereo image, called perception characteristics sets. Secondly, random forest learning method is utilized to simulate HVS mechanism and fuse these features, and then a model is built for evaluating stereo image quality. By applying the proposed model to stereo image test database, experimental results demonstrate that proposed model is consisted with human perception well.