液晶与显示2024，Vol.39Issue(7)：929-938,10.DOI:10.37188/CJLCD.2023-0194
基于Retinex-Net网络模型的渐晕图像校正
Correction of vignetting images based on Retinex-Net network model
摘要
Abstract
During the camera imaging process,a gradual halo effect may occur due to changes in the viewing angle,resulting in a phenomenon of bright in the middle and dark around the image.The presence of gradual halo results in the loss of some edge texture information in the image,greatly affecting the performance of machine vision processing.To address this issue,this article aims to improve the Retinex-Net network model by correcting image clarity and improving denoising performance.Firstly,in order to maintain the high resolution of the corrected image while improving the receptive field,this paper adds dilated convolution on the basis of the original network model.Secondly,the algorithm improves the denoising method to a dense residual network denoising method,with the aim of densely extracting each layer's features of the vignetting image,preserving more of the image's detailed characteristics and suppressing noise.Finally,this article constructs a dataset of vignetting images and verifies the correction performance of the proposed vignetting correction algorithm on the test set.Compared with the original network model before improvement,the algorithm in this paper improves by 0.293 in SSIM value,0.727 in PSNR value,and 0.095 in RMSE value.Compared with correction algorithms such as minimizing image entropy,adaptive compensation Retinex,and radial gradient symmetry,the algorithm in this paper has better correction performance and is more suitable for observation and understanding visually.关键词
渐晕图像校正/Retinex理论/空洞卷积/残差网络Key words
gradual halo image correction/Retinex theory/dilated convolution/residual network分类
信息技术与安全科学引用本文复制引用
黄丹丹,王菲,刘智,高晗,王惠绩..基于Retinex-Net网络模型的渐晕图像校正[J].液晶与显示,2024,39(7):929-938,10.基金项目
国家自然科学基金(No.62127813) （No.62127813）
吉林省科技厅重点研发项目(No.20230201071GX)Supported by National Natural Science Foundation of China(No.62127813) （No.20230201071GX）
Key R&D Project of Jilin Provincial Department of Science and Technology(No.20230201071GX) （No.20230201071GX）
