Fusion of infrared polarization and intensity images using support value transform and fuzzy combination rules

Infrared polarization and intensity imagery provide complementary and discriminative information in image understanding and interpretation. In this paper, a novel fusion method is proposed by effectively merging the information with various combination rules. It makes use of both low-frequency and high-frequency images components from support value transform (SVT), and applies fuzzy logic in the combination process. Images (both infrared polarization and intensity images) to be fused are firstly decomposed into low-frequency component images and support value image sequences by the SVT. Then the low-frequency component images are combined using a fuzzy combination rule blending three sub-combination methods of (1) region feature maximum, (2) region feature weighting average, and (3) pixel value maximum; and the support value image sequences are merged using a fuzzy combination rule fusing two sub-combination methods of (1) pixel energy maximum and (2) region feature weighting. With the variables of two newly defined features, i.e. the low-frequency difference feature for low-frequency component images and the support-value difference feature for support value image sequences, trapezoidal membership functions are proposed and developed in tuning the fuzzy fusion process. Finally the fused image is obtained by inverse SVT operations. Experimental results of visual inspection and quantitative evaluation both indicate the superiority of the proposed method to its counterparts in image fusion of infrared polarization and intensity images.     

Use of chemical etching of CR-39 foils at elevated temperature for fast neutron personnel monitoring in India

CR-39 Solid State Nuclear Track Detecting foils (SSNTD), along with 1 mm thick polyethylene radiator, sealed in triple laminated pouches, are used for country wide Fast Neutron Personnel Monitoring in India. With the present system of processing by elevated temperature electrochemical etching (ETECE) and evaluation using automatic image analysis, only 16 foils are processed at a time and it is useful over the dose equivalent range 0.2 mSv to 10 mSv. It has been reported that, by processing CR-39 of good detection efficiency by chemical etching at elevated temperature, more numbers of foils can be processed simultaneously. In the present study, CR-39 foils from Pershore Moulding (UK) have been chemically etched using 7 N KOH under various conditions of temperature and etching durations and evaluated using high magnification microscope. The duration of chemical etching, has been optimized at a constant temperature of 60°C for chemical etching process. The characteristics of the chemically etched CR-39 foils are compared with the characteristics of the CR-39 foils processed by the existing system of ETECE and the detailed results are presented in the full text of the paper. It has been observed that by chemical etching process, the dose equivalent range of CR-39 foils can be extended above 60 mSv.      

不同变质程度煤的高分辨率透射电镜分析

利用高分辨率透射电子显微镜(HRTEM)分析了三种不同变质程度煤样的结构特征。基于傅里叶-反傅里叶变换方法,并结合Matlab、Arcgis和Auto CAD软件,通过图像分析技术,获得了HRTEM照片的晶格条纹参数。结果表明,三种煤样的晶格条纹呈现不同特征,按条纹长度分别归属于1×1-8×8共计八个类型。以3×3为临界点,在1×1和2×2中,ML-8中芳香层片的比例高于DP-4和XM-3;在3×3-8×8中,ML-8中芳香层片的比例低于DP-4和XM-3。对比HRTEM和XRD参数d002发现,随着镜质组反射率的增加d002都呈现递减趋势。     

Target extraction from blurred trace infrared images with a superstring galaxy template algorithm

Accurate and efficient targets extraction from blurred trace infrared images has very important meaning for latent trace evidence collection in crime scene. Based on the superstring theory, a superstring galaxy template extraction algorithm for infrared trace target is presented. First, all of the pixels are divided into three classes: target pixels, background pixels and blurred pixels. Next, the superstring template characteristics for every pixel in a blurred infrared image are calculated as the features of each pixel. Finally, a galaxy covering algorithm is proposed, target pixels and background pixels are used for training the galaxy covering domain of every galaxy classifiers, and these classifiers will divide each blurred pixel into two classes: a target pixel or a background pixel. Experimental results indicate that the superstring galaxy template algorithm can improve the target extraction rate and reduce the extraction error rate.     

Wall shear stress and near-wall convective transport: Comparisons with vascular remodelling in a peripheral graft anastomosis

Fluid dynamic properties of blood flow are implicated in cardiovascular diseases. The interaction between the blood flow and the wall occurs through the direct transmission of forces, and through the dominating influence of the flow on convective transport processes. Controlled, in vitro testing in simple geometric configurations has provided much data on the cellular-level responses of the vascular walls to flow, but a complete, mechanistic explanation of the pathogenic process is lacking. In the interim, mapping the association between local haemodynamics and the vascular response is important to improve understanding of the disease process and may be of use for prognosis. Moreover, establishing the haemodynamic environment in the regions of disease provides data on flow conditions to guide investigations of cellular-level responses.     

Depth-adaptive regularized reconstruction for reflection diffuse optical tomography

We study reflection diffuse optical tomography using two-dimensional (2D) continuous-wave source-detector arrays on the surface of semi-infinite medium, aiming at imaging the perfusion and the hemoglobin oxygen saturation variation of human cerebral cortex with brain activation. We had previously formulated the inverse problem with Moore-Penrose inversion. When we use simple regularization in this inverse problem, the reconstruction sensitivity decreases markedly with the depth so that the signal in the deep range may be masked by an unwanted signal in the shallow range. In this paper, we propose a depth-adaptive regularized reconstruction, in which we assign a smaller regularization parameter with the depth. We demonstrate improvement of the three-dimensional (3D) reconstruction uniformity using the proposed scheme.     

基于粗糙集与小波变换的图像融合算法

粗糙集理论是处理不确定性问题的数学方法，本文提出了基于粗糙集与小波变换相结合的图像融合算法。该方法首先将粗糙集理论应用于图像滤波中，对含有椒盐噪声的图像进行粗糙中值滤波，然后对滤波后的图像进行小波融合。实验结果表明，粗糙中值滤波有较强的去噪能力，且较好地保持了图像的细节信息，在此基础上进行小波融合，使得融合结果图像具有良好的效果。     

Segmentation of synthetic aperture radar image using multiscale information measure-based spectral clustering

A multiscale information measure （MIM）, calculable from per-pixel wavelet coefficients, but relying on global statistics of synthetic aperture radar （SAR） image, is proposed. It fully exploits the variations in speckle pattern when the image resolution varies from course to fine, thus it can capture the intrinsic texture of the scene backscatter and the texture due to speckle simultaneously. Graph spectral segmen- tation methods based on MIM and the usual similarity measure are carried out on two real SAR images. Experimental results show that MIM can characterize texture information of SAR image more effectively than the commonly used similarity measure.     

Copyright protection in digital museum based on digital holography and discrete wavelet transform

A new method to protect the copyright of digital museum based on digital holography is proposed. The Fresnel hologram of watermark image is embedded in the object to be protected through discrete wavelet transform （DWT）. After the watermark detection, the copyright information appears in the reconstructed hologram. With the higher redundancy feature in the hologram, the proposed technique can actually survive several kinds of image processing. Experimental results prove that the presented method has good robustness in image protection.     

A novel pose and illumination robust face recognition with a single training image per person algorithm

In the real-world application of face recognition system, owing to the difficulties of collecting samples or storage space of systems, only one sample image per person is stored in the system, which is so-called one sample per person problem. Moreover, pose and illumination have impact on recognition performance. We propose a novel pose and illumination robust algorithm for face recognition with a single training image per person to solve the above limitations. Experimental results show that the proposed algorithm is an efficient and practical approach for face recognition.