针对现有超分辨率算法重建后的红外图像存在对比度差、信噪比低、视觉效果模糊的缺点, 提出一种基于视觉对比度特性的红外图像超分辨率重建算法。该算法首先利用人眼在不同灰度级的分辨能力不同, 通过引入红外图像对比度这一先验信息重建红外图像, 其次构建一噪声度量因子以区分图像目标与噪声, 然后对目标边缘进行增强, 噪声进行滤除。实验结果表明:经过改进算法重建的超分辨率红外图像对比度提高了 2倍, 噪声得到了有效抑制, 视觉效果明显改善。

In order to avoid these disadvantages like poor contrast, low signal-to-noise ratio, and blurry visual effect of infrared images reconstructed using the existing super-resolution image reconstruction methods, an improved reconstruction algorithm of infrared images is proposed based on human visual system. The algorithm introduces the contrast as prior information to reconstruct infrared images based on just noticeable difference, which projects objects interested to the ranges where human eyes are sensitive. Then create a measurement factor to distinguish project points and noise points to enhance the edge information of objects and filter noises. It is concluded from experimental results that the contrast of infrared images reconstructed has increased to double as the original value and the noise is eliminated. Visual effects of images obtained by the new method are improved dramatically.