中文摘要：

超级决定(SR ) 增加图象分辨率的一种广泛地使用的技术正在使用算法的方法。然而，保存本地边结构和视觉质量在红外线(红外) 因为他们的劣势， SR 图象正在质问例如详细的缺乏，差的对比，和模糊的边。传统、先进的方法维持量的措施，但是他们主要没能保存边和视觉质量。这份报纸基于高频率层特征建议一个算法。这个算法在重建过程集中于 IR 图象边质地。IR 图象的吝啬的坡度由建议算法重建了的试验性的结果表演分别地基于 L1 标准， L2 标准，和传统的混合标准比传统的算法的到 1.5， 1.4，和 1.2 次增加了。重建的图象的山峰 signal-to-noise 比率，结构的类似索引，和视觉效果也改善了。

英文摘要：

Super-resolution （SR） is a widely used tech- nology that increases image resolution using algorithmic methods. However, preserving the local edge structure and visual quality in infrared （IR） SR images is challenging because of their disadvantages, such as lack of detail, poor contrast, and blurry edges. Traditional and advanced methods maintain the quantitative measures, but they mostly fail to preserve edge and visual quality. This paper proposes an algorithm based on high frequency layer features. This algorithm focuses on the IR image edge texture in the reconstruction process. Experimental results show that the mean gradient of the IR image reconstructed by the proposed algorithm increased by 1.5, 1.4, and 1.2 times than that of the traditional algorithm based on L1- norm, L2-norm, and traditional mixed norm, respectively. The peak signal-to-noise ratio, structural similarity index, and visual effect of the reconstructed image also improved.