华侨大学学报（自然科学版）2026，Vol.47Issue(2)：222-234,13.DOI:10.11830/ISSN.1000-5013.202510026
面向无标记显微细胞图像增强的混合自适应多尺度感知驱动网络
Hybrid Adaptive Multi-Scale Perception-Driven Network for Label-Free Microscopic Cell Image Enhancement
摘要
Abstract
Aiming at the problems of the lack of standard paired data in label-free microscopic cell images,as well as the low contrast,insufficient brightness and blurred cell edge details in labeled microscopic cell images,a hybrid adaptive multi-scale perception-driven network is proposed for label-free microscopic cell image en-hancement.First,a hybrid adaptive Retinex module is designed to perform illumination optimization and struc-tural preserving preprocessing for label-free microscopic cell images.Second,a multi-scale illumination decom-position module is emplyed to separate high-frequency and low-frequency regions of the illumination compo-nent,obtaining illumination sensitivity coefficients and local noise levels of the image.Third,a dynamic Gam-ma parameter prediction module is constructed based on a lightweight CNN to generate a spatially variant Gam-ma correction mechanism,enabling pixel-level adaptive correction.Finally,an adaptive noise detection en-hancement module dynamically selects enhancement strategies according to the entropy value of the reflection component,effectively suppressing noise amplification.Experiments results show that the proposed method outperforms existing enhancement methods in terms of key quantitative metrics(NIQE,MV,IE),verifying its effectiveness in improving the visual quality of label-free microscopic cell images.关键词
自适应Retinex/无标记显微细胞图像/图像增强/光照分解/噪声抑制Key words
adaptive Retinex/label-free microscopic cell image/image enhancement/illumination decomposi-tion/noise suppression分类
信息技术与安全科学引用本文复制引用
孙浩,张富举,雷昊翔,洪岚,傅玉青,杜永兆..面向无标记显微细胞图像增强的混合自适应多尺度感知驱动网络[J].华侨大学学报（自然科学版）,2026,47(2):222-234,13.基金项目
福建省财政拨款项目(5032501) （5032501）
