基于四阶PDEs和对比度增强的荧光显微图像去噪

Fluorescence Microscopic Image Denoising Based on Fourth-Order PDEs and Contrast Enhancement

提出一种用于荧光显微图像去噪扩散模型的算法。该算法针对二阶偏微分方程去噪模型易引起的"块效应"和伪边缘等问题,采用正则化方法,利用四阶偏微分方程,同时融合对比度增强技术设计去噪模型。与二阶偏微分方程扩散模型相比,该算法不仅使去噪图像看起来更加自然清晰,而且在峰值信噪比和结构相似度等客观评价方法下也取得了更加满意的结果。

A new denoising diffusion model is proposed for fluorescence microscopic images, in which fourth-order partial differential equations （PDEs） and contrast enhancement are utilized to overcome the blocky effect and false edges usually caused by second-order PDEs. Compared with second-order PDEs model, the proposed model shows superior performance in terms of both objective criteria and subjective human vision via processing simulated and experimental noisy images.