基于红外焦平面阵列读出结构的非均匀校正算法

空间固定图案噪声严重影响了红外探测器的成像质量，它主要是由于焦平面阵列上各探测单元对于同一辐照的光电响应不完全一致所造成。另外，多通道图像数据采集电路的非均匀性更加重了这种噪声。本文提出了一种基于红外焦平面阵列读出结构的非均匀校正算法，它将校正过程分成两步。首先利用恒定统计方法滤除由通道放大器引起的固定图案噪声，然后再将处理结果通过改进的神经网络方法，进一步校正由探测器响应而产生的非均匀性。由于该算法是递推进行，并且具有收敛速度快、计算复杂度低等优点，因此易于工程实现。文中详细阐述了算法的基本原理及其流程，并用仿真数据和真实红外数据对算法性能进行验证，取得了较好的效果。

Nonuniformity Correction Algorithm Based on the Infrared Focal Plane Array Readout Architecture

The performance of an infrared imaging system is affected by spatial fixed-pattern noise, which is mainly due to the different photoresponse of each detector in a focal plane array for the same irradiance. In addition, the nonuniformity of the readout, which is involved in multichannel image data processing, causes the further noise. A novel nonuniformity correction algorithm based on the infrared focal plane array readout architecture is developed, which corrects the aggregate nonuniformity by two separate steps. First, the nonuniformity from the readout amplifiers is corrected by using the constant statistics method. Second, the noise resulting from the detectors is eliminated by exploiting the improved neural network method. The strength of the proposed algorithm lies in its high convergent speed and low computational complexity, and the performance is demonstrated with both simulated and real infrared imagery.