Universidade Federal do Rio de Janeiro, Rio de Janeiro 21945-970, Brazil.
IEEE Trans Image Process. 2012 Dec;21(12):4758-69. doi: 10.1109/TIP.2012.2218820. Epub 2012 Sep 13.
Infrared focal-plane array (IRFPA) detectors suffer from fixed-pattern noise (FPN) that degrades image quality, which is also known as spatial nonuniformity. FPN is still a serious problem, despite recent advances in IRFPA technology. This paper proposes new scene-based correction algorithms for continuous compensation of bias and gain nonuniformity in FPA sensors. The proposed schemes use recursive least-square and affine projection techniques that jointly compensate for both the bias and gain of each image pixel, presenting rapid convergence and robustness to noise. The synthetic and real IRFPA videos experimentally show that the proposed solutions are competitive with the state-of-the-art in FPN reduction, by presenting recovered images with higher fidelity.
红外焦平面阵列（IRFPA）探测器存在固定模式噪声（FPN），这会降低图像质量，也称为空间不均匀性。尽管 IRFPA 技术最近取得了进展，但 FPN 仍然是一个严重的问题。本文提出了新的基于场景的校正算法，用于连续补偿 FPA 传感器中的偏置和增益非均匀性。所提出的方案使用递归最小二乘法和仿射投影技术，共同补偿每个图像像素的偏置和增益，具有快速收敛性和对噪声的鲁棒性。合成和真实的 IRFPA 视频实验表明，所提出的解决方案在 FPN 减少方面具有竞争力，可提供更高保真度的恢复图像。
