多层级及对比度提升的红外和可见光图像融合

提出了一种针对红外和可见光图像的有效融合算法。首先，在Petrovi?多层级图像融合体系的基础上，在特征级信息中加入高频边缘分量，提高了融合质量；其次，分析了图像特点及目标的物理特性，提出了针对融合结果的对比度提升方法，进一步了提高融合质量。通过主观观察以及客观指标对比证明，该方法获得了优于其他比较方法的融合结果，并且对比度提升方法明显提高了各类方法的红外和可见光图像融合质量，效果好，具有广泛的适用性。

Visible and infrared image fusion based on multi-level method and image contrast improvement

An effective infrared and visible image fusion algorithm was propased. Based on Petrovi? multi-level image fusion system, firstly, it was enriched with the edge components from high-frequency information to get higher image quality. Secondly, a method to enhance the contrast of the fused image which make a further improvement in the image quality by analyzing characteristics and the physical characteristics of the targets in infrared and visible images was given. The subjective observation and comparison of objective indexes prove together that the proposed algorithm does a better job than other comparing methods and the contrast enhancement method can be widely used and improve the visible and infrared fused images' quality obviously.