Infrared thermal imaging denoising method based on second-order channel attention mechanism
Infrared thermal imaging denoising method based on second-order channel attention mechanism
复制标题
基于二阶通道注意力机制的红外热成像去噪方法
DOI：
10.1016/j.infrared.2021.103789
复制
发表时间：
2021-05-25
影响因子：
3.3
通讯作者：
Cheng, Lianglun
中科院分区：
文献类型：
--
作者：
Li, Zhuo;Luo, Shaojuan;Cheng, Lianglun
We propose a deep learning (DL) image denoising method to solve the problem of poor image quality and serious noise interference in the infrared thermal imaging. We develop a DL model to process the image, fit the noise residual of the image and remove the noise from the original image to get a clear image. The model adopts the convolutional neural network (CNN) architecture and uses the second-order attention mechanism and non-local modules at the regional level to improve the extraction of image features and fit the noise residual. We implement experiments on four different datasets to analyze the performance of the algorithm in different noise environments. The experimental results show that the proposed method can effectively remove the noise in the infrared image, performs well in different types of noise, and retain a lot of image details.
