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| 1 | Medical image segmentation using improved FCM显示文摘Image segmentation is one of the most important problems in medical image processing,and the existence of partial volume effect and other phenomena makes the problem much more complex.Fuzzy C-means,as an effective tool to deal with PVE,however,is faced with great challenges in efficiency.Aiming at this,this paper proposes one improved FCM algorithm based on the histogram of the given image,which will be denoted as HisFCM and divided into two phases.The first phase will retrieve several intervals on which to compute cluster centroids,and the second one will perform image segmentation based on improved FCM algorithm.Compared with FCM and other improved algorithms,HisFCM is of much higher efficiency with satisfying results.Experiments on medical images show that HisFCM can achieve good segmentation results in less than 0.1 second,and can satisfy real-time requirements of medical image processing. | ZHANG XiaoFeng ZHANG CaiMing TANG WenJing WEI ZhenWen | 2012 | Science China(Information Sciences)2012，55，5： | 20 |
| 2 | Research on big data applications in Global Energy Interconnection显示文摘Construction of Global Energy Interconnection(GEI) is regarded as an effective way to utilize clean energy and it has been a hot research topic in recent years. As one of the enabling technologies for GEI, big data is accompanied with the sharing, fusion and comprehensive application of energy related data all over the world. The paper analyzes the technology innovation direction of GEI and the advantages of big data technologies in supporting GEI development, and then gives some typical application scenarios to illustrate the application value of big data. Finally, the architecture for applying random matrix theory in GEI is presented. | Dongxia Zhang Robert Caiming Qiu | 2018 | Global Energy Interconnection2018，1，3： | 9 |
| 3 | Image denoising and deblurring: non-convex regularization, inverse diffusion and shock filter显示文摘A large number of applications in image processing and computer vision depend on image quality. In this paper, main concerns are image denoising and deblurring simultaneously in a restoration task by three types of methodologies: non-convex regularization, inverse diffusion and shock filter. We discuss their relations in the context of image deblurring: the inverse diffusion implied by the non-convex regularization, and the superior ability of deblurring edge of the shock filter to that of the inverse diffusion, both in 1D and 2D cases. Finally, we propose a region-based adaptive anisotropic diffusion with shock filter method, which shows advantages of deblurring edges, denoising and smoothing contours in experiments, compared with some related methods. Therein an idea of 'divide and rule' is introduced. | FU ShuJun 1,2,3 , ZHANG CaiMing 2 & TAI XueCheng 3,4 1 School of Mathematics, Shandong University, Jinan 250100, China 2 School of Computer Science and Technology, Shandong University, Jinan 250101, China 3 School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore 639798, Singapore 4 Department of Mathematics, University of Bergen, Bergen 5008, Norway | 2011 | Science China(Information Sciences)2011，54，6： | 8 |
| 4 | Cubic surface fitting to image by combination显示文摘We present a new method for constructing a fitting surface to image data. The new method is based on a supposition that the given image data are sampled from an original scene that can be represented by a surface defined by piecewise quadratic polynomials. The surface representing the original scene is known as the original surface in this paper. Unlike existing methods, which generally construct the fitting surface to the original surface using image data as interpolation data, the new method constructs the fitting surface using the image data as constraints to reverse the sampling process, which improves the approximation precision of the fitting surface. Associated with each data point and its near region, the new method constructs a quadratic polynomial patch locally using the sampling formula as constraint. The quadratic patch approximates the original surface with a quadratic polynomial precision. The fitting surface which approximates the original surface is formed by the combination of all the quadratic polynomial patches. The experiments demonstrate that compared with Bi-cubic and Separable PCC methods, the new method produced resized images with high precision and good quality. | LI XueMei ZHANG CaiMing YUE YiZhen WANG KunPeng | 2010 | Science China(Information Sciences)2010，53，7： | 7 |
| 5 | Adaptive bidirectional diffusion for image restoration显示文摘A large number of applications in image processing and computer vision depend on image quality. In this paper, combining the forward diffusion with the backward diffusion by different weights, we present an adaptive bidirectional diffusion method for image denoising and deblurring simultaneously. Further, we introduce a gradient factor into the data fidelity term, which forms a spatially varying constraint and allows a better restoration of image edges and fine details. In order to obtain a stable solution, we develop a numerically stable scheme and give its theoretical analysis. Finally, we show advantages of this method in deblurring edges, denoising and restoring fine details of image compared with other related methods in experiments. | FU ShuJun ZHANG CaiMing | 2010 | Science China(Information Sciences)2010，53，12： | 5 |
| 6 | Smooth fractal surfaces derived from bicubic rational fractal interpolation functions显示文摘Dear editor,Fractal geometry is an important and active branch of nonlinear science.It has attracted more and more attention[1,2].As an important research field of fractal geometry,fractal interpola- | Fangxun BAO Xunxiang YAO Qinghua SUN Yunfeng ZHANG Caiming ZHANG | 2018 | Science China(Information Sciences)2018，61，9： | 3 |
| 7 | High-resolution images based on directional fusion of gradient显示文摘This paper proposes a novel method for image magnification by exploiting the property that the intensity of an image varies along the direction of the gradient very quickly. It aims to maintain sharp edges and clear details. The proposed method first calculates the gradient of the low-resolution image by fitting a surface with quadratic polynomial precision. Then,bicubic interpolation is used to obtain initial gradients of the high-resolution(HR) image. The initial gradients are readjusted to find the constrained gradients of the HR image, according to spatial correlations between gradients within a local window. To generate an HR image with high precision, a linear surface weighted by the projection length in the gradient direction is constructed. Each pixel in the HR image is determined by the linear surface. Experimental results demonstrate that our method visually improves the quality of the magnified image. It particularly avoids making jagged edges and bluring during magnification. | Liqiong Wu Yepeng Liu Brekhna Ning Liu Caiming Zhang | 2016 | Computational Visual Media2016，2，1： | 3 |
| 8 | A nonlocal gradient concentration method for image smoothing显示文摘It is challenging to consistently smooth natural images, yet smoothing results determine the quality of a broad range of applications in computer vision. To achieve consistent smoothing, we propose a novel optimization model making use of the redundancy of natural images, by defining a nonlocal concentration regularization term on the gradient. This nonlocal constraint is carefully combined with a gradientsparsity constraint, allowing details throughout the whole image to be removed automatically in a datadriven manner. As variations in gradient between similar patches can be suppressed effectively, the new model has excellent edge preserving, detail removal,and visual consistency properties. Comparisons with state-of-the-art smoothing methods demonstrate the effectiveness of the new method. Several applications,including edge manipulation, image abstraction,detail magnification, and image resizing, show the applicability of the new method. | Qian Liu Caiming Zhang Qiang Guo Yuanfeng Zhou | 2015 | Computational Visual Media2015，1，3： | 2 |
| 9 | Kernel-blending connection approximated by a neural network for image classification显示文摘This paper proposes a kernel-blending connection approximated by a neural network(KBNN)for image classification.A kernel mapping connection structure,guaranteed by the function approximation theorem,is devised to blend feature extraction and feature classification through neural network learning.First,a feature extractor learns features from the raw images.Next,an automatically constructed kernel mapping connection maps the feature vectors into a feature space.Finally,a linear classifier is used as an output layer of the neural network to provide classification results.Furthermore,a novel loss function involving a cross-entropy loss and a hinge loss is proposed to improve the generalizability of the neural network.Experimental results on three well-known image datasets illustrate that the proposed method has good classification accuracy and generalizability. | Xinxin Liu Yunfeng Zhang Fangxun Bao Kai Shao Ziyi Sun Caiming Zhang | 2020 | Computational Visual Media2020，6，4： | 2 |
| 10 | Improved fuzzy clustering for image segmentation based on a low-rank prior显示文摘Image segmentation is a basic problem in medical image analysis and useful for disease diagnosis.However,the complexity of medical images makes image segmentation difficult.In recent decades,fuzzy clustering algorithms have been preferred due to their simplicity and efficiency.However,they are sensitive to noise.To solve this problem,many algorithms using non-local information have been proposed,which perform well but are inefficient.This paper proposes an improved fuzzy clustering algorithm utilizing nonlocal self-similarity and a low-rank prior for image segmentation.Firstly,cluster centers are initialized based on peak detection.Then,a pixel correlation model between corresponding pixels is constructed,and similar pixel sets are retrieved.To improve efficiency and robustness,the proposed algorithm uses a novel objective function combining non-local information and a low-rank prior.Experiments on synthetic images and medical images illustrate that the algorithm can improve efficiency greatly while achieving satisfactory results. | Xiaofeng Zhang Hua Wang Yan Zhang Xin Gao Gang Wang Caiming Zhang | 2021 | Computational Visual Media2021，7，4： | 2 |
| 11 | Brief review of image denoising techniques显示文摘With the explosion in the number of digital images taken every day,the demand for more accurate and visually pleasing images is increasing.However,the images captured by modern cameras are inevitably degraded by noise,which leads to deteriorated visual image quality.Therefore,work is required to reduce noise without losing image features(edges,corners,and other sharp structures).So far,researchers have already proposed various methods for decreasing noise.Each method has its own advantages and disadvantages.In this paper,we summarize some important research in the field of image denoising.First,we give the formulation of the image denoising problem,and then we present several image denoising techniques.In addition,we discuss the characteristics of these techniques.Finally,we provide several promising directions for future research. | Linwei Fan Fan Zhang Hui Fan Caiming Zhang | 2019 | Visual Computing for Industry,Biomedicine,and Art2019，2，1： | 2 |
| 12 | Fairing spline curves and surfaces by minimizing energy显示文摘 | Zhang Caiming Zhang Pifu Cheng Fuhua | 2001 | Computer- Aided Design2001，33，13： | 1 |
| 13 | Fairing spline curves and surfaces by minimizing energy 显示文摘 | Zhang Caiming Zhang Pifu Cheng Fuhua | 2001 | Computer-Aided Design2001，33，13： | 1 |
| 14 | Construction of cubic para- metric curve based on minimum energy restriction 显示文摘 | Li Peipei Zhang Caiming | 2007 | China Graphics2007，，： | 1 |
| 15 | Fairing splinecurves and surfaces by minimizing energy显示文摘 | Zhang Caiming Zhang Pifu Cheng Fuhua | 2001 | Computer-Ai-ded Design2001，33，： | 1 |
| 16 | Fairing spline curves and surfaces by minimizing energy显示文摘 | Zhang Caiming Zhang Pifu Cheng Fuhua | 2001 | Computer- Aided Design2001，33，13： | 1 |
| 17 | Constrained scaling of trimmed NURBS surfaces based on fix-and-stretch approach显示文摘 | Zhang Caiming Zhang Pifu Cheng Fuhua | 2001 | Computer-Aided Design2001，33，1： | 1 |
| 18 | Salt and pepper noise removal in surveillance video based on low-rank matrix recovery显示文摘This paper proposes a new algorithm based on low-rank matrix recovery to remove salt &pepper noise from surveillance video. Unlike single image denoising techniques, noise removal from video sequences aims to utilize both temporal and spatial information. By grouping neighboring frames based on similarities of the whole images in the temporal domain, we formulate the problem of removing salt &pepper noise from a video tracking sequence as a lowrank matrix recovery problem. The resulting nuclear norm and L1-norm related minimization problems can be efficiently solved by many recently developed methods. To determine the low-rank matrix, we use an averaging method based on other similar images. Our method can not only remove noise but also preserve edges and details. The performance of our proposed approach compares favorably to that of existing algorithms and gives better PSNR and SSIM results. | Yongxia Zhang Yi Liu Xuemei Li Caiming Zhang | 2015 | Computational Visual Media2015，1，1： | 1 |
| 19 | Removing local irregularities of NURBS surfaces by modifying highlight lines 显示文摘 | Zhang Caiming Cheng Fuhua | 1998 | CAD1998，30，12： | 1 |
| 20 | Formula for computing knots with minimum stress and stretching energies显示文摘Computing knots for a given set of data points in a plane is one of the key steps in the construction of fitting curves with high precision. In this study, a new method is proposed for computing a parameter value(knot) for each data point. With only three adjacent consecutive data points, one may not determine a unique interpolation quadratic polynomial curve, which has one degree of freedom(a variable). To obtain a better curve, the stress and stretching energies are used to optimize this variable so that the quadratic polynomial curve has required properties, which ensure that when the three consecutive points are co-linear, the optimal quadratic polynomial curve constructed is the best. If the position of the mid-point of the three points lies between the first point and the third point, the quadratic polynomial curve becomes a linear polynomial curve. Minimizing the stress and stretching energies is a time-consuming task. To avoid the computation of energy minimization, a new model for simplifying the stress and stretching energies is presented. The new model is an explicit function and is used to compute the knots directly, which greatly reduces the amount of computation. The knots are computed by the new method with minimum stress and stretching energies in the sense that if the knots computed by the new method are used to construct quadratic polynomial,the quadratic polynomial constructed has the minimum stress and stretching energies. Experiments show that the curves constructed using the knots generated by the proposed method result in better interpolation precision than the curves constructed using the knots by the existing methods. | Xuemei LI Fan ZHANG Guoning CHEN Caiming ZHANG | 2018 | Science China(Information Sciences)2018，61，5： | 1 |
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