一种有向图中求取强分图和单项分图的算法

给出一种通过有向图可达矩阵求取强分图和单向分图的方法,此方法回避了结点的次序问题.

由邻接矩阵求解强分图

从图在计算机中的基本表示方式——邻接矩阵出发,给出求解图的邻接矩阵、路径矩阵、强分图的算法。该算法结构简单、形式统一,有一定实用价值。

求解有向图中三个分图问题的研究

强分图、单向分图和弱分图都是研究有向图的子图的连通性问题,求解强分图的算法有很多。总结了强分图的求解算法,主要是算法实现的基本技术和特点;通过论述求解单向分图和相应无向图的团问题的等价性,提出了求解单向分图问题是NP问题的观点;最后又阐述了求解弱分图的方法,并给出了一个具体的算法。

求可达矩阵的简捷算法——轮流做媒法

介绍了采用邻接矩阵作关系矩阵解有向图的可达矩阵的一种简捷算法———轮流做媒法．

An improved detail enhancement algorithm based on difference curvature and contrast field

The gradient image is always sensitive to noise in image detail enhancement. To overcome this shortage, an improved detail enhancement algorithm based on difference curvature and contrast field is proposed. Firstly, the difference curvature is utilized to determine the amplification coefficient instead of the gradient. This new amplification function of the difference curvature takes more neighboring points into account, it is therefore not sensitive to noise. Secondly, the contrast field is nonlinearly amplified according to the new amplification coefficient. And then, with the enhanced contrast field, we construct the energy functional. Finally, the enhanced image is reconstructed by the variational method. Experimental results of standard testing image and industrial X-ray image show that the proposed algorithm can perform well on increasing contrast and sharpening edges of images while suppressing noise at the same time.

An Approach to Underwater Image Enhancement Based on Image Structural Decomposition

Underwater imaging posts a challenge due to the degradation by the absorption and scattering occurred during light propagation as well as poor lighting conditions in water medium Although image filtering techniques are utilized to improve image quality effectively, problems of the distortion of image details and the bias of color correction still exist in output images due to the complexity of image texture distribution. This paper proposes a new underwater image enhancement method based on image struc- tural decomposition. By introducing a curvature factor into the Mumford_Shah_G decomposition algorithm, image details and struc- ture components are better preserved without the gradient effect. Thus, histogram equalization and Retinex algorithms are applied in the decomposed structure component for global image enhancement and non-uniform brightness correction for gray level and the color images, then the optical absorption spectrum in water medium is incorporate to improve the color correction. Finally, the en- hauced structure and preserved detail component are re.composed to generate the output. Experiments with real underwater images verify the image improvement by the proposed method in image contrast, brightness and color fidelity.

Estimation of Knock Wheel Noise of Rail Transport with an Acoustic Intensity Method

The application of railway wheel noise compensation method is considered. The effect can be obtained by shift a pair of usual parallel rail joints on a pair of offset rail joints, for example, the right rail joint is shifted concerning the left rail joint on the certain distance. The distance is depend on the speed of train and promotes the correlation interconnection between excited acoustical pulses. The intensity wheel knock spectrograms corresponding of different distance between rail joints registered by the microphone are estimated. The spectrograms considerably differed from each other in low frequency band are analyzed. The result of practical using the acoustic noise compensation method is proved.

Estimation of coal particle size distribution by image segmentation

Several industrial coal processes are largely determined by the distribution of particle sizes in their feed.Currently these parameters are measured by manual sampling,which is time consuming and cannot provide real time feedback for automatic control purposes.In this paper,an approach using image segmentation on images of overlapped coal particles is described.The estimation of the particle size distribution by number is also described.The particle overlap problem was solved using image enhancement algorithms that converted those image parts representing material in lower layers to black.Exponential high-pass filter(EHPF) algorithms were used to remove the texture from particles on the surface.Finally,the edges of the surface particles were identified by morphological edge detection.These algorithms are described in detail as is the method of extracting the coal particle size.Tests indicate that using more coal images gives a higher accuracy estimate.The positive absolute error of 50 random tests was consistently less than 2.5% and the errors were reduced as the size of the fraction increased.

Research on Novel Natural Image Reconstruction and Representation Algorithm based on Clustering and Modified Neural Network

In this paper, we conduct research on the novel natural image reconstruction and representation algorithm based on clustenng and modified neural network. Image resolution enhancement is one of the earliest researches of single image interpolation. Although the traditional interpolation and method for single image amplification is effect, but did not provide more useful information. Our method combines the neural network and the clustering approach. The experiment shows that our method performs well and satisfactory.

关于可达矩阵的求法探讨

在<离散数学>、<图论>课程中,用矩阵表示图时,涉及到一类重要的矩阵--可达矩阵,它是判别图中任意两点是否有通路的重要手段,也是求强分图的重要方法,但是可达矩阵的求法比较复杂.本文针对这一问题,对可达矩阵的求法进行了改进,提出了一种简单可行的算法.

Split graphs whose half-strong endomorphisms form a monoid

In this paper, the half-strong, the locally strong and the quasi-strong endomorphisms of a split graph are investigated. Let X be a split graph and let End（X）, hEnd（X）, 1End（X） and qEnd（X） be the endomorphism monoid, the set of all half-strong endomorphisms, the set of all locally strong endomorphisms and the set of all quasi-strong endomorphisms of X, respectively. The conditions under which hEnd（X） forms a submonoid of End（X） are given. It is shown that 1End（X） = qEnd（X） for any split graph X. The conditions under which 1End（X） （resp. qEnd（X）） forms a submonoid of End（X） are also given. In particular, if hEnd（X） forms a monoid, then 1End（X） （resp. qEnd（X）） forms a monoid too.

A multiphase texture segmentation method based on local intensity distribution and Potts model

Because texture images cannot be directly processed by the gray level information of individual pixel,we propose a new texture descriptor which reflects the intensity distribution of the patch centered at each pixel.Then the general multiphase image segmentation model of Potts model is extended for texture segmentation by adding the region information of the texture descriptor.A fast numerical scheme based on the split Bregman method is designed to speed up the computational process.The algorithm is efficient,and both the texture descriptor and the characteristic functions can be implemented easily.Experiments using synthetic texture images,real natural scene images and synthetic aperture radar images are presented to give qualitative comparisons between our method and other state-of-the-art techniques.The results show that our method can accurately segment object regions and is competitive compared with other methods especially in segmenting natural images.