Kim Byeong Hak, Kim Min Young, Chae You Seong
School of Electronics Engineering, Kyungpook National University, 80 Daehakro, Bukgu, Daegu 41566, Korea.
Hanwha Systems Coporation, 244, 1 Gongdanro, Gumi, Gyeongsangbukdo 39376, Korea.
Sensors (Basel). 2017 Dec 27;18(1):60. doi: 10.3390/s18010060.
Unmanned aerial vehicles (UAVs) are equipped with optical systems including an infrared (IR) camera such as electro-optical IR (EO/IR), target acquisition and designation sights (TADS), or forward looking IR (FLIR). However, images obtained from IR cameras are subject to noise such as dead pixels, lines, and fixed pattern noise. Nonuniformity correction (NUC) is a widely employed method to reduce noise in IR images, but it has limitations in removing noise that occurs during operation. Methods have been proposed to overcome the limitations of the NUC method, such as two-point correction (TPC) and scene-based NUC (SBNUC). However, these methods still suffer from unfixed pattern noise. In this paper, a background registration-based adaptive noise filtering (BRANF) method is proposed to overcome the limitations of conventional methods. The proposed BRANF method utilizes background registration processing and robust principle component analysis (RPCA). In addition, image quality verification methods are proposed that can measure the noise filtering performance quantitatively without ground truth images. Experiments were performed for performance verification with middle wave infrared (MWIR) and long wave infrared (LWIR) images obtained from practical military optical systems. As a result, it is found that the image quality improvement rate of BRANF is 30% higher than that of conventional NUC.
无人机（UAV）配备有光学系统，包括红外（IR）相机，如光电红外（EO/IR）、目标捕获与指示瞄准具（TADS）或前视红外（FLIR）。然而，从红外相机获得的图像会受到诸如死像素、线条和固定模式噪声等噪声的影响。非均匀性校正（NUC）是一种广泛应用于减少红外图像噪声的方法，但它在去除操作过程中出现的噪声方面存在局限性。已经提出了一些方法来克服NUC方法的局限性，如两点校正（TPC）和基于场景的NUC（SBNUC）。然而，这些方法仍然受到非固定模式噪声的困扰。本文提出了一种基于背景配准的自适应噪声滤波（BRANF）方法来克服传统方法的局限性。所提出的BRANF方法利用了背景配准处理和鲁棒主成分分析（RPCA）。此外，还提出了图像质量验证方法，该方法可以在没有真实地面图像的情况下定量测量噪声滤波性能。使用从实际军事光学系统获得的中波红外（MWIR）和长波红外（LWIR）图像进行了性能验证实验。结果发现，BRANF的图像质量提升率比传统NUC高30%。
