Review:A survey for image resizing

Image resizing is a key technique for displaying images on different devices, and has attracted much attention in the past few years. This paper reviews the image resizing methods proposed in recent years, gives a detailed comparison on their performance, and reveals the main challenges raised in several important issues such as preserving an important region, minimizing distortions, and improving efficiency. Furthermore, this paper discusses the research trends and points out the possible hotspots in this field. We believe this survey can give some guidance for researchers from relevant research areas, offering them an overall and novel view.     

基于缝裁剪和变形的图像缩放方法

提出一种既能保持图像重要内容又能较好地保持重要物体形状的图像缩放算法。该方法结合传统的缝裁剪技术和变形技术来对图像进行缩放。首先利用当前公认效果良好的基于图模型的流形排序显著性检测算法得到图像的显著度图,结合图像梯度能量等信息来构造结构更为清晰的图像重要度图;其次利用之前构造的图像重要度图并按缩放尺度的大小来确定适当的缩放方法;最后根据度量比较结果来选择经典缝裁剪方法或基于能量优化的变形方法进行图像缩放。对比实验结果表明,该方法在图像缩放时能保持重要内容和显著物体形状结构。     

基于Wallis与距离权重增强的无人机影像拼接缝消除

针对无人机影像拼接缝消除困难的问题,提出了一种基于Wallis匀光和距离权重增强的拼接缝消除算法。首先,应用Wallis匀光消除亮度差异,给出Wallis参数设置方法。然后,提出了一种基于空间相关性的距离权重分配方法,通过增强距离对权重的影响,对拼接缝处的局部纹理错位进行全局优化,起到渐入渐出的平滑过渡效果,消除纹理拼接缝。最后,选取7种不同类型影像对本文方法和其他4种经典算法进行对比,并对8条行带影像进行拼接。实验结果表明：本文算法能高效地消除由于曝光差异与几何变形引起的拼接缝,适用于无人机影像快速处理。     

Empirical comparison of image retrieval color similarity methods with human judgment

It is important to verify assumptions and methods of image retrieval against actual human behavior. A study was conducted to compare similarity methods of color histograms against human assessment of similarity. The similarity methods tested include basic histogram intersection, center histogram matching, locality histogram matching, and size-weighted histogram matching. 161 subjects participated in the empirical study. The findings, based on Spearman correlation analysis, showed that both the basic histogram intersection method and size-weighted histogram are very close to human assessment of similarity (Spearman correlation coefficient of 0.915). The other two are not close to human judgment on similarity. This study illustrates an alternative approach to evaluating matching algorithms. Unlike the usual measures of recall and precision, this approach emphasizes human validation. Fewer images are required with the use of statistical testing.     

基于DEM的SAR影像直接与间接正射校正方法比较

对基于DEM的SAR影像直接校正与间接校正方法的原理、步骤、校正效果与适用性进行了比较,并利用正射校正过的高精度光学卫星影像作为基准影像,对两种方法的校正精度进行验证与比较。分析表明,两种方法所采用的校正模型相同,但出发点不同,校正步骤与复杂度也不同,最终校正效果也不一样,但精度没有差很多,都能满足常规SAR正射校正精度需求,在实际应用中需要根据实际情况选择合适的方法。     

A novel level set method for image segmentation by incorporating local statistical analysis and global similarity measurement

This paper presents a novel level set method for complex image segmentation, where the local statistical analysis and global similarity measurement are both incorporated into the construction of energy functional. The intensity statistical analysis is performed on local circular regions centered in each pixel so that the local energy term is constructed in a piecewise constant way. Meanwhile, the Bhattacharyya coefficient is utilized to measure the similarity between probability distribution functions for intensities inside and outside the evolving contour. The global energy term can be formulated by minimizing the Bhattacharyya coefficient. To avoid the time-consuming re-initialization step, the penalty energy term associated with a new double-well potential is constructed to maintain the signed distance property of level set function. The experiments and comparisons with four popular models on synthetic and real images have demonstrated that our method is efficient and robust for segmenting noisy images, images with intensity inhomogeneity, texture images and multiphase images.     

The integration of directional information and local region information for accurate image segmentation

The original local binary fitting (LBF) model is sensitive to contour initialization and thus easily obtains an inaccurate result due to improper initialization. This paper presents a new method that not only can arrive at sub-pixel accuracy, but also allows for more flexible initialization of the contour. Two important terms play main role in our new method. One is an image gradient alignment term (IGA) which uses the directional information of the image gradient, the other is a local intensity fitting term (LIF) which makes use of local region information. The integration of the above two terms prevents our method from being sensitive to contour initialization. In addition, a global intensity fitting term (GIF) multiplied by a stopping function is included, which can speed up our algorithm while do not influence the accuracy of the segmentation result. Using the simple central difference, the gradient descend flow equation for the level set function can be easily and efficiently implemented. The results on several synthetic and real images demonstrate the effectiveness and accuracy of our method.     

Realizations of BELS as WIV method in both direct and indirect closed-loop system identification

The bias eliminated least squares (BELS) method, which is known as efficient for unknown parameter estimation of transfer function in the correlated noise case, has been developed and applied effectively to the closed-loop system identification. In this paper, under the general settings, the realizations of the BELS method as a weighted instrumental variables (WIV) method in both direct and indirect closed-loop system identification are established through constructing an appropriate weighting matrix in the WIV method. The constructed structures are similar in both cases, which reveals that all the proof procedures of the two realizations are the same. Thus, the unified realizations of the BELS as the WIV method for the closed-loop system identification can be built. A simulation example is given to validate our theoretical analysis. Supported by the National Natural Science Foundation of China for Distinguished Young Scholars (Grant No. 60625104), the Ministerial Foundation of China (Grant No. A2220060039), and the Fundamental Research Foundation of BIT (Grant No. 1010050320810)     

Efficient decomposition methods of fuzzy relation and their application to image decomposition

Two optimizations for decomposition problem of fuzzy relation (image) are proposed. The first optimization is a fast decomposition method of fuzzy relation based on the properties of max and min operations and the simultaneous updating of the prototype. The second optimization corresponds to an improvement of a cost function, in order to obtain a good quality of the solution of the decomposition problem.     

A numerical investigation of direct and indirect closed-loop architectures for estimating nonminimum-phase zeros

ABSTRACT

This paper presents a numerical investigation of three direct architectures and three indirect architectures for identifying a plant operating in closed loop. Motivated by adaptive control of systems with nonminimum-phase (NMP) zeros and taking advantage of the fact that zeros are not moved by feedback, the performance metric is the accuracy of the estimates of the NMP zeros of the plant. Assuming known plant order, single-input, single-output, infinite-impulse-response models are constructed in the presence of process and sensor noise. Least squares provides the baseline estimation technique, and prediction error methods are used to account for correlation between the model input and noise. The goal is to compare the accuracy of the NMP-zero estimates obtained from each method and for each architecture.     

Assessing direct and indirect economic impacts of a flood event through the integration of spatial and computable general equilibrium modelling

In this paper we developed and tested an integrated methodology for assessing direct and indirect economic impacts of flooding. The methodology combines a spatial analysis of the damage to the physical stock with a general economic equilibrium approach using a regionally-calibrated (to Italy) version of a Computable General Equilibrium (CGE) global model. We applied the model to the 2000 Po river flood in Northern Italy. To account for the uncertainty in the induced effects on regional economies, we explored three disruption and two recovery scenarios. The results highlight that: i) the flood event produces indirect losses in the national economic system, which are a significant share of the direct losses, and ii) the methodology is able to capture both positive and negative economic effects of the disaster in different areas of the same country. The assessment of indirect impacts, in particular, is essential for a full understanding of the economic outcomes of natural disasters.     

Aggregation of direct and indirect judgments in pairwise comparison matrices with a re-examination of the criticisms by Bana e Costa and Vansnick

In a recent paper by Bana e Costa and Vansnick [C.A. Bana e Costa, J.C. Vansnick, A critical analysis of the eigenvalue method used to derive priorities in AHP, European Journal of Operational Research 187 (3) (2008) 1422-1428], analytic hierarchy process (AHP), particularly its eigenvector method (EM) used for deriving priorities from pairwise comparison matrices, was criticized for the violation of a so-called condition of order preservation (COP). Due to this violation, the EM was considered to have a serious fundamental weakness which makes the use of AHP as a decision support tool very problematic. The consistency ratio (CR) index in the AHP was also criticized for its failure to act as an alert of this violation of COP. In this paper, we look into decision makers’ overall judgments which can be obtained through the aggregation of their direct and indirect judgments and then re-examine Bana e Costa and Vansnick’s numerical examples with a detailed analysis to show the invalidity of their criticisms.     

活动轮廓的演化控制及其在铁谱图像分割中的应用

为了提高活动轮廓(active contour,AC)对边缘特征局部极小值的搜索效率,从而提高其对铁谱图像的分割速度,提出了一种基于活动轮廓评价和演化行为控制的图像分割方法.首先,设计了一种基于矢量图的边缘指示函数(edge indicator,EI)的计算方法,相应的计算结果为活动轮廓模型建立了一个边缘指向更加明确的边缘指示场(edge indicator field,EIF).其次,设计了曲线EI值的无迹卡尔曼滤波模型,并基于此提出了活动轮廓边缘特征的跟踪和评价方法.最后,根据以上评价结果调整曲线模型的参数以控制其演化行为.这种参数调节机制保证了曲线模型参数在不同的区域具有不同的参数设置.试验结果表明,该算法显著地提高了控制演化过程的灵活性以及活动轮廓的收敛速度,并且它能够实现对各种形状磨粒的准确分割,不仅避免了弱边界区域的泄漏现象,而且能够有效滤除背景中的各种噪声干扰和非磨粒目标.     

Clustering and aggregation of relational data with applications to image database categorization

In this paper, we introduce a new algorithm for clustering and aggregating relational data (CARD). We assume that data is available in a relational form, where we only have information about the degrees to which pairs of objects in the data set are related. Moreover, we assume that the relational information is represented by multiple dissimilarity matrices. These matrices could have been generated using different sensors, features, or mappings. CARD is designed to aggregate pairwise distances from multiple relational matrices, partition the data into clusters, and learn a relevance weight for each matrix in each cluster simultaneously. The cluster dependent relevance weights offer two advantages. First, they guide the clustering process to partition the data set into more meaningful clusters. Second, they can be used in subsequent steps of a learning system to improve its learning behavior. The performance of the proposed algorithm is illustrated by using it to categorize a collection of 500 color images. We represent the pairwise image dissimilarities by six different relational matrices that encode color, texture, and structure information.     

Using image processing technology and mathematical algorithm in the automatic selection of vocal cord opening and closing images from the larynx endoscopy video

The human larynx is an important organ for voice production and respiratory mechanisms. The vocal cord is approximated for voice production and open for breathing. The videolaryngoscope is widely used for vocal cord examination. At present, physicians usually diagnose vocal cord diseases by manually selecting the image of the vocal cord opening to the largest extent (abduction), thus maximally exposing the vocal cord lesion. On the other hand, the severity of diseases such as vocal palsy, atrophic vocal cord is largely dependent on the vocal cord closing to the smallest extent (adduction). Therefore, diseases can be assessed by the image of the vocal cord opening to the largest extent, and the seriousness of breathy voice is closely correlated to the gap between vocal cords when closing to the smallest extent. The aim of the study was to design an automatic vocal cord image selection system to improve the conventional selection process by physicians and enhance diagnosis efficiency. Also, due to the unwanted fuzzy images resulting from examination process caused by human factors as well as the non-vocal cord images, texture analysis is added in this study to measure image entropy to establish a screening and elimination system to effectively enhance the accuracy of selecting the image of the vocal cord closing to the smallest extent.     

Biological shape characterization for automatic image recognition and diagnosis of protozoan parasites of the genus Eimeria

We describe an approach of automatic feature extraction for shape characterization of seven distinct species of Eimeria, a protozoan parasite of domestic fowl. We used digital images of oocysts, a round-shaped stage presenting inter-specific variability. Three groups of features were used: curvature characterization, size and symmetry, and internal structure quantification. Species discrimination was performed with a Bayesian classifier using Gaussian distribution. A database comprising 3891 micrographs was constructed and samples of each species were employed for the training process. The classifier presented an overall correct classification of 85.75%. Finally, we implemented a real-time diagnostic tool through a web interface, providing a remote diagnosis front-end.     

Demand-driven image transmission with levels of detail and regions of interest

In this paper, we introduce a formal model which describes consistently levels of detail and regions of interest for the progressive transmission of raster images. This model serves as the foundation of a wavelet-based image communication framework which supports the progressive, redundancy-free transmission of multiple, possibly overlapping regions of interest in an image. To support demand-driven transmission, we introduce a method for interleaving control commands with the embedded bit stream. Since the dyadic wavelet decomposition allows the image resolutions in x and y direction to differ at most by a factor of two, we propose a new wavelet decomposition scheme which raises this number to a power of two for increased flexibility. We discuss some applications including the rectangular fish eye view, a focus and context display technique for raster images which efficiently uses this transmission method and saves screen real-estate.     

基于张量积扩散与纹理元相似的医学图像检索

针对医学图像检索中相似性表达的自身困难,以及噪声影响的问题,提出一种通过张量积图进行扩散,利用其他数据点的上下信息改进基于纹理元的成对相似性度量的方法。首先,采用纹理元的统计方法进行医学图像特征描述和提取,并通过对纹理元相似性加权,得到图像的成对相似性;然后,利用张量积图沿着数据点的内在流形进行相似性的传播,实现全局的相似性度量。在ImageCLEFmed 2009上的实验结果表明,该算法与基于Gabor的检索算法相比,其类平均精度提高了32%,与基于尺度不变特征转换(SIFT)的检索算法相比,其类平均精度提高了19%,能良好地应用于医学图像检索。     

Design and formal proof of a new optimal image segmentation program with hypermaps

This article presents the design of a new functional 2D image segmentation algorithm by cell merging in a subdivision, its proof of total correctness, and the derivation of an optimal imperative program. The planar subdivisions are modeled by hypermaps. The formal specifications of hypermaps and segmentation are developed in the Calculus of Inductive Constructions. The proofs are assisted by the Coq system. The final program is written in C.     

Efficient image restoration of virtual machines with reference count based rewriting and caching

Virtual machine (VM) image backups have duplicate data blocks distributed in different physical addresses, which occupy a large amount of storage space in a cloud computing platform (Choo et al.,  [1] and González-Manzano et al.,  [2]). Deduplication is a widely used technology to reduce the redundant data in a VM backup process. However, deduplication always causes the fragmentation of data blocks, which seriously affects the VM restoration performance. Current approaches often rewrite data blocks to accelerate image restoration, but rewriting could cause significant performance overhead because of frequent I/O operations. To address this issue, we have found that the reference count is a key to the fragmentation degree from a series of experiments. Thus, we propose a reference count based rewriting method to defragment VM image backups, and a caching method based on the distribution of rewritten data blocks to restore VM images. Compared with existing studies, our approach has no interfere to the deduplication process, needs no extra storage, and efficiently improves the performance of VM image restoration. We have implemented a prototype to evaluate our approach in our real cloud computing platform OnceCloud. Experimental results show that our approach can reduce about 57% of the dispersion degree of data blocks, and accelerate about 51% of the image restoration of virtual machines.