基于偏微分方程的低照度图像泊松噪声去除方法  

Study on Poisson Noise Removal Method for Low Illumination Image Based on Partial Differential Equation

作　　者：程书红[1] CHENG Shuhong(School of Information Management,Minnan University of Science and Technolog,Shishi Fujian 362700,China)

机构地区：[1]闽南理工学院信息管理学院,福建石狮362700

出　　处：《重庆科技学院学报（自然科学版）》2023年第4期60-64,共5页Journal of Chongqing University of Science and Technology：Natural Sciences Edition

基　　金：2020年福建省中青年教师教育科研项目“常微分方程在智能化生态系统中的研究”(JAT200743)。

摘　　要：在图像泊松噪声去除过程中,若强行增加噪声分离阈值,将导致所得图像的细节信息损失严重,从而无法保证原始图像的信息完整度。为此,提出基于偏微分方程的低照度图像泊松噪声去除方法。通过低照度偏微分方程的图像边缘模型构建、低照度像素修正与噪声像素融合、泊松噪声偏微分方程模型构建、泊松噪声剪切波变换去除等4个方面,实现了低照度图像泊松噪声的完整去除,且最大化地保留了噪声原始区域的细节信息。通过实例数据的对比测试,证明了该方法的可行性和有效性。In the process of image poisson noise removal,if the noise separation threshold is forcibly increased,the detail information of the obtained image will be seriously lost,and the information integrity of the original image cannot be guaranteed.Therefore,a poisson noise removal method for low illumination images based on partial differential equations is proposed.The complete removal of Poisson noise in low-illuminance images and the maximum preservation of the original noise region details are achieved through the construction of the image edge model of the low illumination partial differential equation,the fusion of low illumination pixel correction and noise pixel,the construction of poisson noise partial differential equation model and the removal of poisson noise shear wave transformation.The feasibility and effectiveness of the proposed method are proved by the comparative test of the example data.

关 键 词：偏微分方程 低照度图像 泊松噪声 噪声去除 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置]