Reconstructing Binary Textured Images by Mean Field Technique

汪涛; 何志均; 俞瑞钊

您当前的位置：

首页 >

文章列表页 >

Reconstructing Binary Textured Images by Mean Field Technique

更新时间：2025-12-08

- Reconstructing Binary Textured Images by Mean Field Technique
- Acta Electronica Sinica Issue 4, (1994)
- 作者机构：
  
  杭州浙江大学计算机系
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN919.8
- Published：1994
- 稿件说明：
移动端阅览
[1]汪涛,何志均,俞瑞钊.二值纹理图象重建的平均场技术[J].电子学报,1994(04):39-45.

汪涛, 何志均, 俞瑞钊. Reconstructing Binary Textured Images by Mean Field Technique[J]. Acta Electronica Sinica, 1994, (4).
[1]汪涛,何志均,俞瑞钊.二值纹理图象重建的平均场技术[J].电子学报,1994(04):39-45. DOI：

汪涛, 何志均, 俞瑞钊. Reconstructing Binary Textured Images by Mean Field Technique[J]. Acta Electronica Sinica, 1994, (4). DOI：

摘要

根据平均场神经网络，本文提出了一种二值纹理图象重建算法。纹理图象用马尔可夫随机场模型描述，重建算法是一个自适应过程，递归地进行模型参数估计和图象重建，平均场方法将图象搜索中基于模拟降温的统计松驰方程转化为一组确定性方程，从而有效地提高了计算效率。计算机实验结果证实了重建算法的有效性。

Abstract

In this Paper

we present a reconstruction method for binary textured images using a mean field technique. The textured image is modeled as a realization of Markov random fields. The reconstruction algorithm is an adaptive process that recursively performs the parameter estimation and the image reconstruction.The mean field method converts the stochastic equation characterized by the simulated annealing into the deterministic equation

and thus efficiently reduces the computational time. A set of simulations are given to show its performance.

关键词

Keywords

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

A Markov Random Field Model for Line Elements and Its Reconstruction

Radar Active Electromagnetic Interference Visual Detection and Parameter Estimation Method

Parameter Estimation for Logistic Model by ParticleSwarm Optimization Algorithm

Parameter Estimation of 3D Scattering Centers Based on CP-GTD Model

A Fast Algorithm for Mono-Component PPS Parameter Estimation

Related Author

Wang Tao

Zhuang Xinhua & Xing Xiaoliang

邢小良

ZHU Xuan

RUAN Jiang-jun

WU Hao

SHI Zhao-peng

HE Fang-min

Related Institution

Dept. of Computer Science & Engineering, Zhejiang University

浙江大学计算机科学与工程系杭州 310027

School of Electrical Engineering and Automation, Wuhan University

National Key Laboratory of Electromagnetic Energy, Naval University of Engineering

School of Electronic Information and Communications, Huazhong University of Science and Technology

⁰