中国光学（中英文）2024，Vol.17Issue(1)：160-166,7.DOI:10.37188/CO.2023-0059
基于光照模型的细胞内镜图像不均匀光照校正算法
Non-uniform illumination correction algorithm for cytoendoscopy images based on illumination model
摘要
Abstract
Cytoendoscopy requires continuous amplification with a maximum magnification rate of about 500 times.Due to optical fiber illumination and stray light,the image has non-uniform illumination that changes with the magnification rate,which affects the observation and judgement of lesions by doctors.Therefore,we propose an image non-uniform illumination correction algorithm based on the illumination model of cytoendoscopy.According to the principle that image information is composed of illumination and reflection components,the algorithm obtains the illumination component of the image through a convolution-al neural network,and realizes non-uniform illumination correction based on the two-dimensional Gamma function.Experiments show that the average gradient of the illumination channel and the discrete entropy of the image are 0.22 and 7.89,respectively,after the non-uniform illumination correction by the proposed method,which is superior to the traditional methods such as adaptive histogram equalization,homophobic filtering,single-scale Retinex and the WSI-FCN algorithm based on deep learning.关键词
细胞内镜/不均匀光照/光照模型/卷积神经网络Key words
cytoendoscopy/non-uniform illumination/illumination model/convolutional neural network分类
信息技术与安全科学引用本文复制引用
邹鸿博,章彪,王子川,陈可,王立强,袁波..基于光照模型的细胞内镜图像不均匀光照校正算法[J].中国光学（中英文）,2024,17(1):160-166,7.基金项目
国家重点研发计划项目(No.2021YFC2400103) （No.2021YFC2400103）
之江实验室科研项目(No.2019MC0AD02,No.2022MG0AL01)Supported by the National Key Research and Development Program of China(No.2021YFC2400103) （No.2019MC0AD02,No.2022MG0AL01）
Key Research Project of Zhejiang Lab(No.2019MC0AD02,No.2022MG0AL01) （No.2019MC0AD02,No.2022MG0AL01）
