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排序方式: 共有113条查询结果,搜索用时 31 毫秒
1.
数字图像修复技术综述   总被引:36,自引:3,他引:33  
图像修复是图像复原研究中的一个重要内容,它的目的是根据图像现有的信息来自动恢复丢失的信息,其可以用于旧照片中丢失信息的恢复、视频文字去除以及视频错误隐藏等。为了使人们对该技术有个概略了解,在对目前有关数字图像修复技术的文献进行理解和综合的基础上,首先通过对数字图像修复问题的描述,揭示了数字图像修复的数学背景;接着分别介绍了以下两类图像修复技术:一类是基于几何图像模型的图像修补(inpainting)技术,该技术特别适用于修补图像中的小尺度缺损;另一类是基于纹理合成的图像补全(comp letion)技术,该技术对于填充图像中大的丢失块有较好的效果;然后给出了这两类方法的应用实例;最后基于对数字图像修复问题的理解,提出了对数字图像修复技术的一些展望。  相似文献
2.
We present a modification of the Mumford-Shah functional and its cartoon limit which facilitates the incorporation of a statistical prior on the shape of the segmenting contour. By minimizing a single energy functional, we obtain a segmentation process which maximizes both the grey value homogeneity in the separated regions and the similarity of the contour with respect to a set of training shapes. We propose a closed-form, parameter-free solution for incorporating invariance with respect to similarity transformations in the variational framework. We show segmentation results on artificial and real-world images with and without prior shape information. In the cases of noise, occlusion or strongly cluttered background the shape prior significantly improves segmentation. Finally we compare our results to those obtained by a level set implementation of geodesic active contours.  相似文献
3.
Nonquadratic variational regularization is a well-known and powerful approach for the discontinuity-preserving computation of optic flow. In the present paper, we consider an extension of flow-driven spatial smoothness terms to spatio-temporal regularizers. Our method leads to a rotationally invariant and time symmetric convex optimization problem. It has a unique minimum that can be found in a stable way by standard algorithms such as gradient descent. Since the convexity guarantees global convergence, the result does not depend on the flow initialization. Two iterative algorithms are presented that are not difficult to implement. Qualitative and quantitative results for synthetic and real-world scenes show that our spatio-temporal approach (i) improves optic flow fields significantly, (ii) smoothes out background noise efficiently, and (iii) preserves true motion boundaries. The computational costs are only 50% higher than for a pure spatial approach applied to all subsequent image pairs of the sequence.  相似文献
4.
An Introduction to Variational Methods for Graphical Models   总被引:12,自引:0,他引:12  
This paper presents a tutorial introduction to the use of variational methods for inference and learning in graphical models (Bayesian networks and Markov random fields). We present a number of examples of graphical models, including the QMR-DT database, the sigmoid belief network, the Boltzmann machine, and several variants of hidden Markov models, in which it is infeasible to run exact inference algorithms. We then introduce variational methods, which exploit laws of large numbers to transform the original graphical model into a simplified graphical model in which inference is efficient. Inference in the simpified model provides bounds on probabilities of interest in the original model. We describe a general framework for generating variational transformations based on convex duality. Finally we return to the examples and demonstrate how variational algorithms can be formulated in each case.  相似文献
5.
Differential methods belong to the most widely used techniques for optic flow computation in image sequences. They can be classified into local methods such as the Lucas–Kanade technique or Bigün's structure tensor method, and into global methods such as the Horn/Schunck approach and its extensions. Often local methods are more robust under noise, while global techniques yield dense flow fields. The goal of this paper is to contribute to a better understanding and the design of novel differential methods in four ways; (i) We juxtapose the role of smoothing/regularisation processes that are required in local and global differential methods for optic flow computation. (ii) This discussion motivates us to describe and evaluate a novel method that combines important advantages of local and global approaches: It yields dense flow fields that are robust against noise. (iii) Spatiotemporal and nonlinear extensions as well as multiresolution frameworks are presented for this hybrid method. (iv) We propose a simple confidence measure for optic flow methods that minimise energy functionals. It allows to sparsify a dense flow field gradually, depending on the reliability required for the resulting flow. Comparisons with experiments from the literature demonstrate the favourable performance of the proposed methods and the confidence measure.  相似文献
6.
Using Prior Shapes in Geometric Active Contours in a Variational Framework   总被引:9,自引:0,他引:9  
In this paper, we report an active contour algorithm that is capable of using prior shapes. The energy functional of the contour is modified so that the energy depends on the image gradient as well as the prior shape. The model provides the segmentation and the transformation that maps the segmented contour to the prior shape. The active contour is able to find boundaries that are similar in shape to the prior, even when the entire boundary is not visible in the image (i.e., when the boundary has gaps). A level set formulation of the active contour is presented. The existence of the solution to the energy minimization is also established.We also report experimental results of the use of this contour on 2d synthetic images, ultrasound images and fMRI images. Classical active contours cannot be used in many of these images.  相似文献
7.
偏微分方程(PDEs)模型在图像处理中的若干应用   总被引:8,自引:2,他引:6  
介绍了偏微分方程(PDEs)模型在图像处理与分析中的应用,基本思想,发展历史和解决问题的基本框架。主要阐述了变分方法和形变模型(曲线演化)在图像恢复和图像分割中的应用。理论和实验结果表明,应用偏微分方程模型进行图像处理是一种有效的工具。最后,分析了这种方法的优点和面临的挑战。  相似文献
8.
We propose a variational framework for the integration of multiple competing shape priors into level set based segmentation schemes. By optimizing an appropriate cost functional with respect to both a level set function and a (vector-valued) labeling function, we jointly generate a segmentation (by the level set function) and a recognition-driven partition of the image domain (by the labeling function) which indicates where to enforce certain shape priors. Our framework fundamentally extends previous work on shape priors in level set segmentation by directly addressing the central question of where to apply which prior. It allows for the seamless integration of numerous shape priors such that—while segmenting both multiple known and unknown objects—the level set process may selectively use specific shape knowledge for simultaneously enhancing segmentation and recognizing shape.  相似文献
9.
三维图像多相分割的变分水平集方法   总被引:7,自引:1,他引:6  
变分水平集方法是图像分割等领域出现的新的建模方法,借助多个水平集函数可有效地实现图像多相分割.但在区域/相的通用表达、不同区域内图像模型的表达、通用的能量函的设计、高维图像分割中的拓展研究等方面仍是图像处理的变分方法、水平集方法、偏微分方程方法等研究的热点问题.文中以三维图像为研究对象,系统地建立了一种新的三维图像多相分割的变分水平集方法.该方法用n-1个水平集函数划分n个区域,并基于Heaviside函数设汁出区域划分的通用的特征函数;其能量泛函包括通用的区域模型、边缘检测模型和水平集函数为符号距离函数的约束项3部分;最后,针对所得到的曲面演化方程,采用半隐式差分格式进行离散,并对多种类型三维图像进行分割验证了所提出模型的通用性和有效性.  相似文献
10.
一种变分自适应中值滤波算法   总被引:5,自引:0,他引:5       下载免费PDF全文
王勋  毕笃彦 《计算机应用》2006,26(9):2059-2062
针对自适应中值和变分滤波方法脉冲噪声去除能力的不足,提出了一种新的变分自适应中值滤波方法。首先采用自适应中值滤波器对脉冲噪点进行标识,然后对标识的噪点构建由逼近条件和边缘保持正则化条件构成的代价函数,通过变分方法对代价函数寻优求解,对噪点进行恢复。最后进行了仿真试验,并与标准中值滤波,开关中值滤波,自适应中值滤波,和变分滤波方法进行了比较。试验结果表明,在信噪比和细节保留方面明显优于上述滤波方法,可以有效去除高达90%的脉冲噪声。  相似文献
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