Chinese Optics Letters, 2007, 5 (2): 74, Published Online: Feb. 8, 2007
A new adaptive nonuniformity correction algorithm for infrared line scanner based on neural networks Download: 543次
图像处理 非均匀性校正 扫描型 红外热像仪 神经网络 自适应 040.3060 Infrared 100.2550 Focal-plane-array image processors 100.2980 Image enhancement 200.4260 Neural networks
Abstract
The striping pattern nonuniformity of the infrared line scanner (IRLS) severely limits the system performance. An adaptive nonuniformity correction (NUC) algorithm for IRLS using neural network is proposed. It uses a one-dimensional median filter to generate ideal output of network and can complete NUC by a single frame with a high correction level. Applications to both simulated and real infrared images show that the algorithm can obtain a satisfactory result with low complexity, no need of scene diversity or global motion between consecutive frames. It has the potential to realize real-time hardware-based applications.
Jing Sui, Liquan Dong, Weiqi Jin, Yayuan Zhang. A new adaptive nonuniformity correction algorithm for infrared line scanner based on neural networks[J]. Chinese Optics Letters, 2007, 5(2): 74.