汪伟, 许德海, 任明艺. 一种改进的红外图像自适应增强方法[J]. 红外与激光工程, 2021, 50(11): 20210086. DOI: 10.3788/IRLA20210086
引用本文: 汪伟, 许德海, 任明艺. 一种改进的红外图像自适应增强方法[J]. 红外与激光工程, 2021, 50(11): 20210086. DOI: 10.3788/IRLA20210086
Wang Wei, Xu Dehai, Ren Mingyi. An improved infrared image adaptive enhancement method[J]. Infrared and Laser Engineering, 2021, 50(11): 20210086. DOI: 10.3788/IRLA20210086
Citation: Wang Wei, Xu Dehai, Ren Mingyi. An improved infrared image adaptive enhancement method[J]. Infrared and Laser Engineering, 2021, 50(11): 20210086. DOI: 10.3788/IRLA20210086

一种改进的红外图像自适应增强方法

An improved infrared image adaptive enhancement method

  • 摘要: 对红外图像而言,如何在压缩动态范围的同时增强细节、抑制噪声以提升显示效果是一个重要的课题。文中提出一种改进的红外图像自适应增强方法,首先设计了一种参数自适应的引导滤波方法,并基于引导滤波将原始红外图像拆分成基本层和细节层;然后基于像素灰度分布设计了一种新型的自适应阈值的直方图映射方法,以对基本层压缩动态范围并增强其对比度;之后利用自适应引导滤波的线性系数对细节层进行增强并抑制噪声;最后对增强后的基本层和细节层进行自适应融合得到增强后的红外图像。实验结果表明,与对比度受限的自适应直方图均衡方法、基于引导滤波的高动态红外图像增强方法等几种效果相对较好的方法相比,文中所提出的方法处理后的图像细节更丰富,噪声抑制效果更强,视觉效果更好,且该方法适应性更强,无须调整参数即可应对多种观测场景。

     

    Abstract: For infrared image, how to enhance the detail and suppress the noise while compressing the dynamic range is an important issue. An improved infrared image adaptive enhancement method was proposed. Firstly, a parameter adaptive guided image filtering method was designed, based on the guided image filtering, the original infrared image was divided into the basic layer and the detail layer; based on the gray distribution, a new histogram projection method with adaptive threshold was designed to compress the dynamic range and enhance the contrast of the basic layer; then the linear coefficient of the adaptive guided filter was used to enhance the detail layer and suppress the noise; finally, the enhanced infrared image was obtained by adaptive fusion of the enhanced basic layer and detail layer. The experimental results show that compared with several good algorithms, such as the contrast limited adaptive histogram equalization and the detail enhancement for high-dynamic-range infrared images based on guided image filter, the proposed algorithm processed image detail is richer, noise suppression effect is stronger, better visual effect, and the algorithm is more flexible, without adjusting parameters to deal with a variety of scenarios.

     

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