Abstract
Microscopy image enhancement plays a pivotal role in understanding the details of biological cells and materials at microscopic scales. In recent years, there has been a significant rise in the advancement of microscopy image enhancement, specifically with the help of deep learning methods. This survey paper aims to provide a snapshot of this rapidly growing state-of-the-art method, focusing on its evolution, applications, challenges, and future directions. The core discussions take place around the key domains of microscopy image enhancement of super-resolution, reconstruction, and denoising, with each domain explored in terms of its current trends and their practical utility of deep learning.
Abstract (translated)
显微图像增强在理解生物细胞和材料的微观细节方面扮演着关键角色。近年来，借助深度学习方法，在显微图像增强领域取得了显著进展。本综述论文旨在概述这一迅速发展的最新技术状态，重点探讨其发展历程、应用、挑战以及未来方向。核心讨论围绕超分辨率、重建和去噪这三个显微图像增强的关键领域展开，每个领域的当前趋势及其在实际中的深度学习实用性都将得到详细探索。
URL
https://arxiv.org/abs/2509.15363
