Image de-noising algorithm based on Gaussian mixture model and adaptive threshold modeling

机译：基于高斯混合模型和自适应阈值建模的图像降噪算法

获取原文

获取原文并翻译 | 示例

页面导航

摘要
著录项
相似文献
相关主题

摘要

In this paper, we conduct research on the image de-noising algorithm based on Gaussian mixture model and adaptive threshold modeling. Minimum spanning tree based on the local threshold value method, can make full use of the image information change itself, by defining a new local threshold method to calculate the regional difference and extracting, gives image a good segmentation and de-noising effect. Gaussian mixture model is a kind of important background modeling method. The method using multiple Gaussian background model is established through the background update constantly adjust background model of the components of the Gaussian distribution, and therefore has a certain ability to adapt. Under this assistance, we integrate the corresponding mode to propose the new image de-noising algorithm that obtains better performance.

机译：本文针对基于高斯混合模型和自适应阈值建模的图像去噪算法进行了研究。基于局部阈值方法的最小生成树，可以充分利用图像信息本身的变化，通过定义新的局部阈值方法来计算区域差异并提取，给图像良好的分割和去噪效果。高斯混合模型是一种重要的背景建模方法。通过背景更新不断建立高斯分布成分的背景模型，建立了使用多个高斯背景模型的方法，因此具有一定的适应能力。在此协助下，我们整合了相应的模式以提出新的图像降噪算法，以获得更好的性能。

著录项

来源
《2017 International Conference on Inventive Computing and Informatics》|2017年|226-229|共4页
会议地点 Coimbatore(IN)
作者
Xinxin Xie; Wenzhun Huang; Harry Haoxiang Wang; Zhe Liu;
展开▼
作者单位

School of Information Engineering, Xijing University, Xi'an, China;

School of Information Engineering, Xijing University, Xi'an, China;

School of Information Engineering, Xijing University, Xi'an, China;

GoPerception Laboratory, Ithaca 14853, NY, USA;

展开▼
会议组织
原文格式 PDF
正文语种 eng
中图分类
关键词
Gaussian mixture model; Adaptation models; Image segmentation; Noise reduction; Image denoising; Conferences;

机译：高斯混合模型适应模型图像分割降噪图像降噪会议;

相似文献

外文文献
中文文献
专利

1. Threshold-Based Adaptive Gaussian Mixture Model Integration (TA-GMMI) Algorithm for Mapping Snow Cover in Mountainous Terrain [J] . Zhang Yonghong, Ma Guangyi, Tian Wei, Computer Modeling in Engineering & Sciences . 2020,第3期

机译：基于阈值的自适应高斯混合模型集成（TA-GMMI）山区地形中雪覆盖的算法
2. A Background Modeling Algorithm Based on Improved Adaptive Mixture Gaussian [J] . Ming Han1, Jiaomin Liu1, Yi Sun2 Journal of Computers . 2013,第9期

机译：基于改进的自适应混合的高斯建模算法
3. Optimal Noise Removal Using an Adaptive Wiener Filter Based on a Locally Stationary Gaussian Mixture Distribution Model for Images [J] . Nobumoto Yamane, Yoshitaka Morikawa, Youichi Kawakami, Electronics and Communications in Japan. Part 3, Fundamental Electronic Science . 2004,第1期

机译：基于局部平稳高斯混合分布模型的自适应维纳滤波器最优噪声去除
4. Image de-noising algorithm based on Gaussian mixture model and adaptive threshold modeling [C] . Xinxin Xie, Wenzhun Huang, Harry Haoxiang Wang, International Conference on Inventive Computing and Informatics . 2017

机译：基于高斯混合模型和自适应阈值建模的图像去噪算法
5. Gaussian Mixture Model based Spatial Information Concept for Image Segmentation. [D] . Nguyen, Thanh Minh. 2011

机译：基于高斯混合模型的空间信息概念用于图像分割。
6. A Local Neighborhood Robust Fuzzy Clustering Image Segmentation Algorithm Based on an Adaptive Feature Selection Gaussian Mixture Model [O] . Hang Ren, Taotao Hu 2020

机译：基于自适应特征选择高斯混合模型的局部邻域鲁棒模糊聚类图像分割算法
7. A background modeling algorithm based on improved adaptive Mixture Gaussian [O] . Ming Hana, Jiaomin Liua, Yi Sunb 2015

机译：一种基于改进自适应混合高斯分布的背景建模算法

Image de-noising algorithm based on Gaussian mixture model and adaptive threshold modeling

摘要

著录项

相似文献

相关主题

期刊订阅