Fusion of infrared-visible images using improved multi-scale top-hat transform and suitable fusion rules

Integration of infrared and visible images is an active and important topic in image understanding and interpretation. In this paper, a new fusion method is proposed based on the improved multi-scale center-surround top-hat transform, which can effectively extract the feature information and detail information of source images. Firstly, the multi-scale bright (dark) feature regions of infrared and visible images are respectively extracted at different scale levels by the improved multi-scale center-surround top-hat transform. Secondly, the feature regions at the same scale in both images are combined by multi-judgment contrast fusion rule, and the final feature images are obtained by simply adding all scales of feature images together. Then, a base image is calculated by performing Gaussian fuzzy logic combination rule on two smoothed source images. Finally, the fusion image is obtained by importing the extracted bright and dark feature images into the base image with a suitable strategy. Both objective assessment and subjective vision of the experimental results indicate that the proposed method is superior to current popular MST-based methods and morphology-based methods in the field of infrared-visible images fusion.     

Non-locally regularized segmentation of multiple sclerosis lesion from multi-channel MRI data

Segmentation of multiple sclerosis (MS) lesion is important for many neuroimaging studies. In this paper, we propose a novel algorithm for automatic segmentation of MS lesions from multi-channel MR images (T1W, T2W and FLAIR images). The proposed method is an extension of Li et al.'s algorithm in [1], which only segments the normal tissues from T1W images. The proposed method is aimed to segment MS lesions, while normal tissues are also segmented and bias field is estimated to handle intensity inhomogeneities in the images. Another contribution of this paper is the introduction of a nonlocal means technique to achieve spatially regularized segmentation, which overcomes the influence of noise. Experimental results have demonstrated the effectiveness and advantages of the proposed algorithm.     

Unique solvability and exponential stability of differential hemivariational inequalities

ABSTRACT

In this paper, we study a differential hemivariational inequality (DHVI, for short) in the framework of reflexive Banach spaces. Our aim is three fold. The first one is to investigate the existence and the uniqueness of mild solution, by applying a general fixed-point principle. The second one is to study its exponential stability, by employing the formula for the variation of parameters and inequality techniques. Finally, the third aim is to illustrate an application of our abstract results in the study of an initial and boundary value problem which describes the contact of an elastic rod with an obstacle.     

Detail enhancement of blurred infrared images based on frequency extrapolation

A novel algorithm for enhancing the details of the blurred infrared images based on frequency extrapolation has been raised in this paper. Unlike other researchers’ work, this algorithm mainly focuses on how to predict the higher frequency information based on the Laplacian pyramid separation of the blurred image. This algorithm uses the first level of the high frequency component of the pyramid of the blurred image to reverse-generate a higher, non-existing frequency component, and adds back to the histogram equalized input blurred image. A simple nonlinear operator is used to analyze the extracted first level high frequency component of the pyramid. Two critical parameters are participated in the calculation known as the clipping parameter C and the scaling parameter S. The detailed analysis of how these two parameters work during the procedure is figure demonstrated in this paper. The blurred image will become clear, and the detail will be enhanced due to the added higher frequency information. This algorithm has the advantages of computational simplicity and great performance, and it can definitely be deployed in the real-time industrial applications. We have done lots of experiments and gave illustrations of the algorithm’s performance in this paper to convince its effectiveness.     

基于用户感性需求的产品设计方案评估方法

目前满足用户的情感诉求和情感体验逐渐成为热销产品的关键属性,引起了产品开发者和企业决策者的关注。为了更好地贴合用户情感体验,结合信息熵、灰色关联分析和模糊TOPSIS,提出了以用户感性需求为向导的产品设计方案的评估方法。首先引入感性工学中复合感性意象量化用户的情感信息,通过对收集的产品意象进行聚类分析和主成分分析产生具有代表性的目标意象,运用语义差分调查获得代表意象的评价值;其次对规范化的意象评价值计算其熵值权重;最后结合灰色关联分析和模糊TOPSIS,产生用户情感信息指导下的产品设计备选方案的优先级排序。以智能手表设计为例,验证了该方法的可行性和有效性。信息熵和结合灰色关联分析的模糊TOPSIS可以较大限度地减少方案评估时的个人主观影响,确保了评估结果的准确性,对企业产品方案决策具有指导意义。     

Can a latent image explain the characteristics of the Shroud body image?

The distribution of the fibrils that have yielded the body image on the Shroud is stochastic. In this paper, we show that the hypothesis of latent image can explain the chemical and physical characteristics of the above body image. It is also concluded that the “Shroud question” requires new radiocarbon dating done on a sample selected after careful chemical analysis.     

遥感干涉超光谱图像压缩编码

基于卫星干涉超光谱成像光谱仪成像原理的分析,提出了一种新的遥感超光谱图像压缩方案，利用成像推扫平移特性提出一种低存储量，帧间小波域匹配的序列压缩，只需存储两帧图像，比起单帧处理提高图像PSNR 3-4dB.为了保护图像的光谱特征，系统采用了一种新的感兴趣区域（Region of interest, ROI） 编码技术，使系统的压缩比提高8倍以上.该感兴趣区域（ROI）编码采用率失真优化斜率提升，而不是比特平面移位，使图像在相同的光谱分辨率下拥有更好的空间分辨率.试验数据表明，算法大大保护了图像的光谱特性，在8倍压缩比情况时，满足卫星干涉超光谱遥感图像要求.     

Simple consistent cluster methods based on redescending M-estimators with an application to edge identification in images

We use the local maxima of a redescending M-estimator to identify cluster, a method proposed already by Morgenthaler (in: H.D. Lawrence, S. Arthur (Eds.), Robust Regression, Dekker, New York, 1990, pp. 105–128) for finding regression clusters. We work out the method not only for classical regression but also for orthogonal regression and multivariate location and show that all three approaches are special cases of a general approach which includes also other cluster problems. For the general case we show consistency for an asymptotic objective function which generalizes the density in the multivariate case. The approach of orthogonal regression is applied to the identification of edges in noisy images.     

被动式自动对焦的数学模型及其机构

为了实现自动对焦 ,用几何光学中的物象关系式建构了镜头位移量与物距的数学模型 ,据此 ,采用光电耦合器件、电压保持电路等电子器件与机械传动部件相结合 ,实现了自动对焦 .对自动对焦系统的设计和维修有一定的参考价值