OALib Journal期刊

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匹配条件: “br>李旭超” ,找到相关结果约446602条。
Expectation maximization method for parameter estimation of image statistical model

Li Xuchao,<br>
中国图象图形学报 , 2012,
Abstract: Expectation maximization (EM)algorithm for parameter estimation of image statistical model is one of the striking research fields in recent decades.Based on the analysis of the EM algorithm,combining the current application research in parameter estimation of image statistical model,analysis and comparison are conducted in terms of the three improvement schemes of standard EM algorithm.In this paper,integrating image restoration,segmentation,object tracking and the fusion of other evolution optimization algorithms,through three aspects,such as the selection of missing data sets,the statistical model establishments of missing and incomplete data sets,and parameter estimation of image statistical models,as well as the advantages and disadvantages of the corresponding EM algorithm are exponded.The structure and complexity of EM algorithm,so far as to success or failure,are directly determined by the selection of missing data and the expression form of incomplete data.In the end,challenges and possible trends are discussed,and extensive applications of EM algorithm to parameter estimation of statistical model with missing data are pointed out.
Survey of Wavelet Domain Image Denoising

LI Xu-chao,ZHU Shan-an,<br>,朱善安
中国图象图形学报 , 2006,
Abstract: Wavelet domain image denoising has been a striking research problem in image processing. In order to give people a summary knowledge of wavelet domain image denoising, based on many literatures of wavelet domain image denoising, this paper attempts to make a survey of wavelet domain image denoising. First, it gives the characteristics of wavelet transformation, and gives the optimization criterion of wavelet domain image denoising, the selection of wavelet basis. Then, describes the methods of image denoising, and analyzes the building model methods capitalized on wavelet coefficients. At the end, the future trend of wavelet domain image denoising is pointed out.
A Survey of the Markov Random Field Method for Image Segmentation

LI Xu-chao,ZHU Shan-an,<br>,朱善安
中国图象图形学报 , 2007,
Abstract: Markov random field method is a very active research field in image segmentation.This paper introduces the relationship between a general theory based on Markov random field method and the images,and provides a general framework in image segmentation,including the construction of spatial and wavelet domain image models,the selection of the optimization criterion,calculation of the number of labeling,parameter estimation of image models and the realization of image segmentation.The applications of image segmentation are reviewed.And a few possible trends are discussed.
Image Denoising Based on Wavelet Modulus Maxima and Neyman-Pearson Principle Threshold

LI Xu-chao,ZHU Shan-an,<br>,朱善安
中国图象图形学报 , 2005,
Abstract: Firstly,this paper gives the property of wavelet transform of two dimensional noise,analyzes the relationship of wavelet transform modulus maxima to different decomposed class j and Lipschitz exponent,and points out how to determine and protect image edges.Then it explains the orthogonal wavelet transform of denoising based on soft and hard threshold,and puts forward a denoising method based on the wavelet modulus maxima and Neyman-Pearson principle. The method finds the optimal trade off between image denoising and protecting image edges.Based on the assumption that the observed image is the sum of the expected image and irregular corruptive noise,the qualitative and quantitative performance of our image denoising method is compared with others.Simulation results show the proposed method can efficiently denoise,such as increasing Signal-to-Noise Ratio(SNR),lowing Mean Square Error(MSE) and Relative Entropy(RE), while preserving the details of the original image.
Application of Ecosystem Services Valuation in Strategic Environmental Assessment for Land-Use Planning in Beijing

XU Xu,LI Xiao-bing,FU Na,LI Chao,<br>许,晓兵,符娜,
资源科学 , 2008,
Abstract: Strategic Environmental Assessment (SEA) is now widely used in the evaluation of policies, plans and strategies. Land-use planning is very important because of its role in land-use and land-cover change (LUCC) which can lead to ecosystem and environmental change. For reasonable and scientific land-use planning and development of an environmentally-friendly society, SEA should be carried out before land-use planning. In this article, the value of ecosystem services was used as an assessment index for conducting a strategic environmental assessment of Beijing land-use planning. The Chinese ecosystem services value per unit area for different ecosystem types, as determined by Xie Gaodi, was used to calculate the total value of ecosystem services in Beijing in 1996, 2006 and 2010. The results of the three years are 187.96×108 yuan, 193.30×108 yuan and 211.87×108 yuan, so the value of ecosystem services in Beijing increased by 23.90×108 yuan from 1996 to 2010. Generally speaking, the land-use plan can be regarded as reasonable because of the increase in value of ecosystem services. Then, we took into account the population explosion of Beijing in recent years. The per-capita ecosystem services value was calculated and the results show that although the total ecosystem services value increased, the value per-capita decreased, from 1492.46 yuan in 1996 to 1 222.64 yuan in 2006 and 211.87 yuan in 2010. When compared with GDP, which increased sharply, the growth rate of ecosystem services value was much slower, and the development of economy and ecological environment were uncoordinated. Thus, land-use planning still has some problems and supplementary modifications are needed. More work should be done on environmental protection and resource utilization. The land-use data for 2006 indicated that more attention should be paid to the actualization of land-use planning. The accuracy of ecosystem services valuation plays an important role in the SEA for land-use planning, and to make a reasonable SEA, more work should be done on the accuracy of valuation, such as thinking about ecosystem heterogeneity and revaluation of construction sites and unused land. This should be the direction and focus of future research.
Image Segmentation Based on Wavelet Domain Hierarchical Markov Model

LI Xu-chao,ZHU Shan-an,ZHU Sheng-li,<br>,朱善安,朱胜利
中国图象图形学报 , 2007,
Abstract: In order to overcome the deficiency of approximation to the wavelet coefficient joint probability with two-state Gaussian mixture model(GMM) and the shortcoming of the independence between wavelet labels in wavelet domain hidden Markov tree model(HMT),a new image segmentation algorithm based on wavelet domain hierarchical Markov model is proposed.The new image model is described as wavelet coefficient joint distribution with finite general mixture model(FGM),while the GMM in HMT model is only one of the FGMs.Vitilizing on the local interactions of labels described by Markov random field(MRF),the label field priori probability model with explicit expression,which overcomes the shortcoming of the independence between labels in the HMT model,is determined.Using Bayes principle,the recursive algorithm of image segmentation is derived.The proposed model inherits not only the characteristics of spatial domain hierarchical MRF model with effective recursive algorithm but also the characteristics of HMT model with the variable Markov parameters in different scales.The experiments with real images and synthetic texture images are carried out,the results show that the proposed method outperforms other standard segmentation methods,such as accurately locating image edges,correctly identifying different regions.
The survey of fuzzy clustering method for image segmentation

Li Xuchao,Liu Haikuan,Wang Fei,Bai Chunyan,<br>,刘海宽,王飞,白春艳
中国图象图形学报 , 2012,
Abstract: The fuzzy c-means (FCM) clustering algorithm for image segmentation is one of the striking research fields in recent decades.Based on the analysis of the FCM algorithm,we combine the current application research in image segmentation,and we analyze and compare it in terms of measuring the expressions of the FCM algorithm.In this paper,through three aspects,such as single-resolution,multi-resolution,and the integration of other algorithms,the advantages and disadvantages of the improved FCM algorithms are expounded.In the end,some challenges and possible trends are discussed.

中国图象图形学报 , 2012, DOI: 10.11834/jig.20120602
Abstract: 期望最大值算法是近年来图像统计模型参数估计技术领域的研究热点之一。在对期望最大值算法分析的基础上,结合其在图像统计模型参数估计中的应用研究,对改变标准期望最大值算法的3种方式进行比较分析。结合图像恢复、分割、目标跟踪以及与其他优化算法的融合应用,从丢失数据集的选取、丢失数据集和不完全数据集统计模型的建立,以及统计模型参数估计3个方面,评述期望最大值算法优缺点。丢失数据的选取和不完全数据的描述形式直接决定期望最大值算法的结构和计算复杂度,以致算法的成败。最后,讨论期望最大值算法目前存在的问题及未来的发展方向,指出其在具有丢失数据统计模型参数估计中广泛应用。
中国图象图形学报 , 2014, DOI: 10.11834/jig.20141204
Abstract: 目的由拟合项与正则项组成的海森矩阵,如果不具有特殊结构,其逆矩阵计算比较困难,为克服此缺点,提出一种海森矩阵可分块对角化的牛顿投影迭代算法。方法首先,用L2范数描述拟合项,用自变量是有界变差函数的复合函数刻画正则项,建立能量泛函正则化模型。其次,引入势函数,将正则化模型转化为增广能量泛函。再次,构造预条件矩阵,使得海森矩阵可分块对角化。最后,为防止牛顿投影迭代算法收敛到局部最优解,采用回溯线性搜索算法和改进的Barzilai-Borwein步长更新准则使得算法全局收敛。结果针对图像去模糊正则化模型容易使边缘平滑和产生阶梯效应“两难”问题,提出一种新的正则化模型和牛顿投影迭代算法。仿真结果表明,“两难”问题通过本文算法得到了很好的解决。结论与其他正则化图像去模糊模型相比,本文算法明显改善图像的质量,如有效地保护图像的边缘,抑制阶梯效应,相对偏差和误差较小,较高的峰值信噪比和结构相似测度。
电子学报 , 2015, DOI: 10.3969/j.issn.0372-2112.2015.10.016
Abstract: 针对非可微有界变差函数容易在图像恢复过程产生阶梯效应,提出一种二阶可微的原始-对偶模型及牛顿迭代算法.分析伪Huber函数的特性,运用Fenchel变换,将原始模型转化为原始-对偶模型,然后提出原始与对偶变量不同步长更新策略的牛顿迭代算法,并给出广义交叉验证准则确定权重.利用点扩散函数和高斯噪声对合成与真实图像进行模糊,将本文方法与快速傅里叶变换算法、快速收缩阈值算法、交替投影算法和拟牛顿算法进行实验对比,仿真表明,本文算法能保护图像的边缘,抑制阶梯效应,取得较小的相对误差、偏差,较高的峰值信噪比、相似度性测度和良好的视觉效果.

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