可见光与红外彩色融合图像感知清晰度评价模型

提出了感知清晰度评价模型，来评价人眼对红外与可见光彩色融合图像细节和边缘的可辨识度。首先，利用人眼对比度敏感函数模型，抑制在特定观察条件下图像中人眼不敏感的频率成分。之后，在局部频带对比度模型基础上，结合人眼亮度掩模特性构造了感知对比度模型。最后，计算融合图像人眼兴趣区域(细节和边缘区域)的感知对比度，进而评价融合图像的感知清晰度。实验结果表明，与现有的五种彩色图像清晰(模糊)度的客观评价模型相比，考虑人眼视觉特性感知清晰度模型的计算结果与人眼主观感受具有较好的一致性，可以有效地对彩色融合图像清晰度进行客观评价。

Perceptual Sharpness Metric for Visible and Infrared Color Fusion Images

For visible and infrared color fusion images, objective sharpness assessment model is proposed to measure the clarity of detail and edge definition of the fusion image. Firstly, the contrast sensitivity functions (CSF) of the human visual system is used to reduce insensitive frequency components under certain viewing conditions. Secondly, perceptual contrast model, which takes human luminance masking effect into account, is proposed based on local band-limited contrast model. Finally, the perceptual contrast is calculated in the region of interest (contains image details and edges) in the fusion image to evaluate image perceptual sharpness. Experimental results show that the proposed perceptual sharpness metrics provides better predictions, which are more closely matched to human perceptual evaluations, than five existing sharpness (blur) metrics for color images. The proposed perceptual sharpness metrics can evaluate the perceptual sharpness for color fusion images effectively.