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Statistical Scene-Based Non-Uniformity Correction Method with Interframe Registration
DOI:10.3390/s19245395.png)
摘要
En 中文
The non-uniform response in infrared focal plane array (IRFPA) detectors inevitably produces corrupted images with a fixed-pattern noise. In this paper, we present a novel and adaptive scene-based non-uniformity correction (NUC) method called Correction method with Statistical scene-based and Interframe Registration (CSIR), which realizes low delay calculation of correction coefficient for infrared image. This method combines the statistical method and registration method to achieve a better NUC performance. Specifically, CSIR estimates the gain coefficient with statistical method to give registration method an appropriate initial value. This combination method not only reduces the need of interactive pictures, which means lower time delay, but also achieves better performance compared to the statistical method and other single registration methods. To verify this, real non-uniformity infrared image sequences collected by ourselves were used, and the advantage of CSIR was compared thoroughly on frame number (corresponding to delay time) and accuracy. The results show that the proposed method could achieve a significantly fast and reliable fixed-pattern noise reduction with the effective gain and offset.
Keyword:
statistical scene
non-uniformity correction
fixed-pattern noise
adaptive
registration method
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期刊
IF:
3.5
论文数:
7.2W
被引数:
20.9W
机构
引用论文
Guided filter and adaptive learning rate based non-uniformity correction algorithm for infrared focal plane array基于引导滤波和自适应学习率的红外焦平面阵列非均匀性校正算法
An Adaptive Deghosting Method in Neural Network-Based Infrared Detectors Nonuniformity Correction基于神经网络的红外探测器非均匀性校正中的自适应去重影方法
SENSORS
IF3.5

