摘要
本文借助非局部均值滤波方法,滤除图像所含噪声的同时兼顾图像细节的保持。在Otus算法分割阈值的基础上,根据图像的灰度级特征构造抑制因子,在增强对比度的同时,适当抑制图像的背景信息,增强图像的目标信息,以达到在增强图像对比度的同时,凸显红外图像中目标信息的效果。以图像的梯度特征为依据,构造梯度调节模型,以达到在增强图像细节内容时,避免过增强和欠增强现象的出现,从而实现红外图像对比度和清晰度的增强。实验结果显示,本文算法增强的红外图像,对比度和清晰度都较好,能够较好地突出红外目标信息。
This article uses the non local mean filtering method to filter out noise in the image while preserving image details.On the basis of Otus algorithm segmentation threshold,suppression factors are constructed based on the grayscale features of the image.While enhancing contrast,the background information of the image is appropriately suppressed,and the target information of the image is enhanced to achieve the effect of highlighting the target information in the infrared image while enhancing image contrast.Based on the gradient features of the image,a gradient adjustment model is constructed to achieve the effect of avoiding over enhancement and under enhancement when enhancing the details of the image,thereby enhancing the contrast and clarity of the infrared image.The experimental results show that the algorithm enhanced infrared images in this paper have good contrast and clarity,and can effectively highlight infrared target information.
作者
李威
朱经睿
黎凯
Li Wei;Zhu Jing-rui;Li Kai(Ji'an College,Jiangxi Ji'an 343000)
出处
《内燃机与配件》
2025年第18期19-21,共3页
Internal Combustion Engine & Parts
基金
2021年度江西省教育厅科学技术研究项目“抑制因子联合梯度调节模型的红外图像增强算法”(GJJ219407)。
关键词
红外图像增强
抑制因子
梯度调节模型
非局部均值滤波
Otus算法
Infrared image enhancement
Inhibitory factor
Gradient adjustment model
Non local mean filtering
Otus algorithm
