西安电子科技大学学报（自然科学版）2019，Vol.46Issue(1)：14-19,6.DOI:10.19665/j.issn1001-2400.2019.01.003
级联残差学习的红外图像非均匀性校正方法
Cascade residual learning method for infrared image nonuniformity correction
摘要
Abstract
Traditional scene adaptive nonuniformity correction methods generally suffer from the over smooth and residual nonuniformity in the corrected results.In view of this,a cascade residual learning based nonuniformity correction method is presented.This method uses the multiscale feature extraction unit to fuse the extracted features and employs the residual learning strategy to deal with the overfitting problem. Experimental results validate that the proposed method yields nearly 5dB improvement in the average peak signal-to-noise ratio(PSNR)as compared to the traditional scene adaptive correction methods.Moreover, its visual effects are clearer and sharper.关键词
深度学习/非均匀性校正/图像去噪/红外图像处理Key words
deep learning/nonuniformity correction/image denoising/infrared image processing分类
信息技术与安全科学引用本文复制引用
赖睿,官俊涛,徐昆然,熊皑,杨银堂..级联残差学习的红外图像非均匀性校正方法[J].西安电子科技大学学报（自然科学版）,2019,46(1):14-19,6.基金项目
国家自然科学基金(61674120) （61674120）
中央高校基本科研业务费专项资金(300102328110,JBG161113) （300102328110,JBG161113）
