李召龙, 沈同圣, 史浩然, 娄树理. 基于场景的红外光学系统渐晕效应校正方法[J]. 红外与激光工程, 2015, 44(S1): 8-12.
引用本文: 李召龙, 沈同圣, 史浩然, 娄树理. 基于场景的红外光学系统渐晕效应校正方法[J]. 红外与激光工程, 2015, 44(S1): 8-12.
Li Zhaolong, Shen Tongsheng, Shi Haoran, Lou Shuli. Scene-based method to correct vignetting effect of IR optical system[J]. Infrared and Laser Engineering, 2015, 44(S1): 8-12.
Citation: Li Zhaolong, Shen Tongsheng, Shi Haoran, Lou Shuli. Scene-based method to correct vignetting effect of IR optical system[J]. Infrared and Laser Engineering, 2015, 44(S1): 8-12.

基于场景的红外光学系统渐晕效应校正方法

Scene-based method to correct vignetting effect of IR optical system

  • 摘要: 渐晕效应是红外成像过程中普遍存在的现象。由于红外成像系统输出的场景亮度或对比度通常较低,所以渐晕效应对成像性能的影响非常严重,因此对渐晕效应的校正也显得尤为重要。对渐晕效应的产生原因做了分析,首先提出了一种渐晕快速校正方法。通过场景之间做差,提取背景信息。用二维高斯函数逼近背景灰度分布,得到较准确的校正因子,从而实现渐晕校正。然后利用方差信息改进了背景提取方法,使方法适用于较复杂的场景。提出像素点差值和的概念来评价校正效果,校正后差值和普遍减小到未校正差值和的1/5到1/2。两种方法均不需要亮度均匀分布的参考背景,即可实现对渐晕效应比较理想的校正。

     

    Abstract: The vignetting effect is a widespread phenomenon in the process of infrared imaging. Because the output brightness or contrast of the infrared imaging system is low, the impact of vignetting effect on the performance of the system is very serious. Therefore, it is particularly important to correct the vignetting effect. The cause of the generation of the vignetting effect was analyzed. Firstly, a fast correction method was proposed. The difference between scene was used to get background information. The background gray level distribution was approximated by the two-dimensional Gauss distribution, and the correction factor was obtained. Then the background extraction method was improved by using the variance information, and the method was applied to a more complex scene. The concept of the sum of pixel difference was presented. After correction, the sum of pixel difference decreaseal to 1/5-1/2 of the sum of pixel difference before correction. The correction effect of the two methods is better without using a reference scene of uniform gray distribution.

     

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