基于恒定统计约束的红外图像序列非均匀性校正

Nonuniformity correction of infrared image sequences using the constant-statistics constraint.

作者信息

Harris J G, Chiang Y M

出版信息

IEEE Trans Image Process. 1999;8(8):1148-51. doi: 10.1109/83.777098.

Abstract

Using clues from neurobiological adaptation, we have developed the constant-statistics (CS) algorithm for nonuniformity correction of infrared focal point arrays (IRFPAs) and other imaging arrays. The CS model provides an efficient implementation that can also eliminate much of the ghosting artifact that plagues all scene-based nonuniformity correction (NUC) algorithms. The CS algorithm with deghosting is demonstrated on synthetic and real infrared (IR) sequences and shown to improve the overall accuracy of the correction procedure.

摘要

利用神经生物学适应性方面的线索，我们开发了用于红外焦平面阵列（IRFPA）和其他成像阵列非均匀性校正的常数统计（CS）算法。CS模型提供了一种高效的实现方式，还能消除困扰所有基于场景的非均匀性校正（NUC）算法的大部分重影伪像。带有去重影功能的CS算法在合成和真实红外（IR）序列上得到了验证，并显示出能提高校正过程的整体精度。