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gibbs model
相关语句
  gibbs模型
     Restoration of high resolution image based on Gibbs model
     基于Gibbs模型的提高图像分辨率方法
短句来源
     Second, is it design one Gibbs model to recover to image, design his parameter choose the mode.
     2.针对图像复原设计了一种Gibbs模型,并设计了其参数选取模式。
短句来源
     Through Gibbs model, can analyse the whole composition of the image from some characteristic of the image, having good convergence efficiency, this has brought convenience for real-time processing;
     通过Gibbs模型,可以从图像的局部特性来分析图像的整体构成,具有良好的收敛效率,这为实时处理带来了方便;
短句来源
     This paper discusses an algorithm based on Markov causal neighborhood, which not only uses Markov/Gibbs model but also generates the new texture image pixel by pixel through a deterministic searching process. This avoids the computational demand of probability sampling so as to develop the efficiency of texture synthesis. As a result, it texture synthesis constrained texture synthesis and motion synthesis possible.
     讨论了一种基于Markov因果邻域系统的纹理综合算法,它使用Markov/Gibbs模型描述纹理,避免了复杂概率函数,通过确定的搜索过程逐像素产生纹理,减小了运算量,提高了纹理综合效率,使纹理综合可以应用在受限纹理综合和运动纹理综合等领域。
短句来源
  吉布斯模型
     The thesis is based mostly on three recent papers on learning gibbs distributions. They are [Zhu 97]'s work on creating a unified statistical framework by minimax entropy principle, which is then used to learn texture images, [Guo 01]'s proposal for learning the distribution of intrinsic texture element (Textons) by gibbs model and [Liu 01]'s introduction of the minimax Entropy idea to the learning of Inhomogeneous Gibbs Model (IGM).
     本论文的基本出发点是基于下面三篇关于吉布斯学习的重要文献,即[Zhu 97]中创造的用最小最大熵准则(Minimax Entropy Principle)学习纹理图像分布的一套统计框架,[Guo 01]中提到的用吉布斯模型学习纹理基元分布的方法,以及[Liu 01]中介绍的关于非均匀吉布斯模型(Inhomogeneous Gibbs Model,简称IGM)的学习机制。
短句来源
     Using Minimax Entropy Gibbs Model to Learn the Distribution of Structural Gibbs Point Process and Random Vector
     用最小最大熵吉布斯模型学习结构化吉布斯点过程以及随机向量分布的研究
短句来源
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  gibbs model
The mean-field model allows us to gain insight into the Gibbs model behavior in the neighborhood of these temperatures.
      
This minimization is an important part of applications that use the Gibbs model within a Bayesian estimation framework for maximum a posteriori (MAP) estimation.
      
The ion chemistry of the streams was influenced by bedrock weathering according to the Gibbs Model.
      
In the case of our model system major deviations were found between optical data and data obtained using the Gibbs model.
      
(3) The Gibbs model of the SML was extended, and the multilayer model of the SML was advanced.
      
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This paper defines the Feature Symbol Random Field(FSRF), while presents a novel FSRF-Gibbs model for texture segmentation.The main function of FSRF is acting as 2D representation of texture feature vectors which come from the multichannel analysis. What should be emphasized is that all the employed features are spatial-changed, i. e. need not to be stable for certain texture region. By employment of FSRF, this poper also isgnificantly eases the problem in model estimation of Markov Random Field(MRF)....

This paper defines the Feature Symbol Random Field(FSRF), while presents a novel FSRF-Gibbs model for texture segmentation.The main function of FSRF is acting as 2D representation of texture feature vectors which come from the multichannel analysis. What should be emphasized is that all the employed features are spatial-changed, i. e. need not to be stable for certain texture region. By employment of FSRF, this poper also isgnificantly eases the problem in model estimation of Markov Random Field(MRF). As a result, finer and more reasonable segmentation is expected by involving both multichannel analysis techniques and fine MRF model. Finally, a new algorithm is included, which is easy to perform and leads to satisfactory experiment results on Bredatz Textures.

本文提出了特征符号随机场的概念,定义了新的特征符号随机场-Gibbs模型,并讨论了它在纹理分割中的应用与传统马尔可夫随机场模型方法相比,由于包容了更多、更细致的图象信息,本文的方法能够得到更精确的分割结果,同时,新模型仍然有比较简单的模型形式,模型估计方法简单、利于在线运用.与传统特征聚类分割方法(如多通道特征聚类分割方法)相比,本文不要求得到相对纹理区域具有稳定性的特征,并利用Gibbs模型来描述空间变化的特征.从而使分割过程基于更本质的纹理特征,使分割结果更具普遍性.本文以标准Brodatz纹理为实验样本,取得了令人满意的实验结果.

This paper defines a novel Gibbs model for texture segmentation. The traditional modelsgenerally take a linear gray spatial-interaction form, which employ interaction parameters as imagefeature. The novel one proposed makes no assumption on gray-pixels' linear spatial-interaction, andmay be a more detailed representation of Markov Random Field. It's also easy to estimate the modelby involving both multichannel analysis techniques and vector quantization algorithm. Finally,several Brodatz texture segmentation...

This paper defines a novel Gibbs model for texture segmentation. The traditional modelsgenerally take a linear gray spatial-interaction form, which employ interaction parameters as imagefeature. The novel one proposed makes no assumption on gray-pixels' linear spatial-interaction, andmay be a more detailed representation of Markov Random Field. It's also easy to estimate the modelby involving both multichannel analysis techniques and vector quantization algorithm. Finally,several Brodatz texture segmentation results are included, which are very satisfactory.

马尔可夫随机场-Gibbs模型在计算机视觉领域,得到了广泛的应用.传统形式的Gibbs模型多以空间灰度信息的线性干涉关系为描述基础.由于实际图像中空间灰度信息的非线性关系,这类模型在诸如多纹理分割这样的应用中,有较大的局限性.本文提出了一种新的Gibbs模型形式,并结合Gabor技术和矢量量化技术来完成模型的估计.该模型具有形式简单、包含信息量大的优点.在利用Brodatz标准纹理进行的分割实验中,得到了理想的分割结果.

The motion compensated technique is one of major technique on the sequence images or real time video signal coding. The technique is used mostly to increase the coding efficiency and quality in modern real time coding standard. At the same time,a lot of scholars are attracted to research the theory and algorithms continuously and deeply. In this paper,an improved algorithm (MFSC) is proposed. First, the fixed block matching is relaxed. Secondly, the correlation of the moving vector between neighboring blocks...

The motion compensated technique is one of major technique on the sequence images or real time video signal coding. The technique is used mostly to increase the coding efficiency and quality in modern real time coding standard. At the same time,a lot of scholars are attracted to research the theory and algorithms continuously and deeply. In this paper,an improved algorithm (MFSC) is proposed. First, the fixed block matching is relaxed. Secondly, the correlation of the moving vector between neighboring blocks is considered fully. The search method of the MFSC algorithm is different to traditional block matching algorithm. The Markov / Gibbs model is used as reference foundation selected moving vector in the moving division of the sub blocks. The smooth moving vector can be obtained by using the grey parameter between inter frame pixels. At the same time,the moving continuity between neighboring areas are considered. The better compensation effect is obtained.

运动补偿是序列图象或实时视频信号编码中的重要技术之一,在现代实时编码标准中多数采用该技术提高编码效率及质量,因此吸引了广大学者对该方法的机理及算法不断进行深入研究。本文针对已有方法的不足提出了一种改进算法—MFSC算法。本算法对运动补偿技术的二个方面进行了改进。一是对固定块的匹配算法进行了改进。其二,本算法充分考虑了相邻块之间运动矢量的相关性。从子块邻域的运动矢量集合中选取矢量作为子块象素的运动矢量。本算法搜索过程中采用Mcrkov/Gibbs模型作为选取运动矢量的参考依据对子块进行运动分割,同时利用帧间象素灰度参数得到较平滑的运动矢量场,并且在补偿中充分考虑了相邻区域之间运动的连续性。MFSC算法在信噪比及块效应方面均有较大提高,取得了较好的补偿效果。

 
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