激光雷达双轴配准度的测试

激光雷达的双轴配准度是影响系统性能的重要指标,提出了系统装配完成后测试激光雷达双轴配准度的方法。对于有延时保护的系统,提出了测试的解决方案。采用模拟回波发生器产生经过序列延时的模拟回波,利用光路调整器将模拟回波与激光雷达发射光轴调平行后,在一定角度范围内偏转回波方向,对激光雷达接收系统进行扫描。根据系统电信号的输出与光束偏转角度的关系判断系统的双轴配准度。对一激光雷达进行了测试,验证了测试系统的可靠性,对系统精度进行了分析,系统误差<45μrad。

有效视野内检查床的变化对SPECT/CT同机配准度的影响

目的探讨检查床位置的变化对SPECT/CT有效视野同机图像配准精度的影响及达到最佳配准效果时检查床的位置。方法采用6个放射性点源153Gd(40.9 kev组、41.54 kev组、103.18 kev组,2个1组,共3个能量峰组)、标准模型,CT断层位置不变,分别通过改变床位与床高,得到13组原始断层数据,利用仪器自带的ALIGNMENT软件获得配准度偏差,比较不同床位与床高配准偏差值。结果最小配准度误差:Z轴在0 cm,Y轴在-4 cm处;即最佳的配准位置。结论进行SPECT断层与CT图像的同机融合,如果两种图像达不到较佳融合,就必须进行图像配准度的质控,必要时进行图像配准度的校准。

一种选择适配区的算法

介绍了适配区的定义和研究意义 ,并就适配区的选择 ,提出了一种基于基准图的可配准特征向量 ,用以描述采用相关匹配算法搜寻指定点时定位的难易程度 ,由此给出了一种选择适配区的方法 ,实验验证了方法的可行性。

一种基于面结构特征的病理切片图像拼接算法

本研究是对“基于相关性的病理切片图像的配准算法”的一种改进算法 ,以面结构特征作为模板 ,采用求配准度的方法寻求图像匹配。算法的速度较快 ,稳定性更高 ,在实验中取得了更为满意的配准效果。

Uncertainty Evaluation of Preparation of Organophosphorus Pesticide Mixed Standard Solution

The uncertainty of standard solution plays an important role in detection of pesticide residues. It may affect the accuracy of detection results. In this study, the 14 organophosphorus pesticides mixed standard solution was used as the material to analyze all the influencing factors for the preparation of mixed standard solution with uncertainty as the only judging index. The preparation uncertainty of mixed standard solution was calculated with the top-down calculation method. In the end, the expanded uncertainty was presented. The results showed that the preparation of mixed standard solution from stock solution with precise pipettes had a relatively low uncertainty.

Accuracy Validation for Medical Image Registration Algorithms:a Review

Accuracy validation is essential to clinical application of medical image registration techniques. Registration validation remains a challenging problem in practice mainly due to lack of 'ground truth'. In this paper, an overview of current validation methods for medical image registration is presented with detailed discussion of their benefits and drawbacks. Special focus is on non-rigid registration validation. Promising solution is also discussed.

A method based on mutual information and gradient information for medical image registration

Mutual information is widely used in medical image registration, because it does not require preprocessing the image. However, the local maximum problem in the registration is insurmountable. We combine mutual information and gradient information to solve this problem and apply it to the non-rigid deformation image registration. To improve the accuracy, we provide some implemental issues, for example, the Powell searching algorithm, gray interpolation and consideration of outlier points. The experimental results show the accuracy of the method and the feasibility in non-rigid medical image registration.

Intensity Allocation Criteria of Carbon Emissions Permits and Regional Economic Development in China——Based on a 30-Province/Autonomous Region Computable General Equilibrium Model

The intensity allocation criteria of carbon emissions permits and its influence on China＇s regional development are analyzed through the 30-province/autonomous region computable general equilibrium （CGE） model. Simulation results show that： industrial intensity criteria without taking regional economic development into account deepen the unbalance of regional economic development; regional intensity criteria without taking industrial properties into account exert little negative impact on regional harmonious development, but relatively high negative influence on high-carbon emission industries. The two-step allocation scheme that the central government allocates emissions permits to provincial governments based on regional economic development and then provincial governments allocate emissions permits to emission resources or entities based on industrial properties is a feasible and operable choice.

Medical Image Registration Based on Phase Congruency and Regional Mutual Information

In this paper, a new approach of muhi-modality image registration is represented with not only image intensity, but also features describing image structure. There are two novelties in the proposed method. Firstly, instead of standard mutual information （ MI ） based on joint intensity histogram, regional mutual information （ RMI ） is employed, which allows neighborhood information to be taken into account. Secondly, a new feature images obtained by means of phase congruency are invariants to brightness or contrast changes. By incorporating these features and intensity into RMI, we can combine the aspects of both structural and neighborhood information together, which offers a more robust and a high level of registration accuracy.

Mutual Information for Image Registration

Image registration is the overlaying of two images of the same scene taken at different times or by different sensors. It is one of the essential steps in information processing in remote sensing. To attain a highly accurate, reliable and low computation cost in image registration a suitable and similarity metric and reduction in search data and search space is required. In this paper, the author shows that if the right bin size is chosen, mutual information can be more robust than correlation in the registration of multi-temporal images. The author also compares the sensitivity of mutual information and correlation to Gaussian and multiplicative speckle noise. The author investigates automatic subimage selection as a reduction in search data strategy. The author proposes a measure, called alienability, which shows the ability ofa subimage to provide reliable registration. Alternate subimage selection methods such as using gradient, entropy and variance are also investigated. The author furthermore looks into a search space strategy using a gradient approach to maximize mutual information and show our first results.

Research on Airborne Terrain Matching System

In view of the airborne application characteristics such as flexible flight, large error of altimeter, large initial error of inertial navigation system, etc., a new terrain matching system architecture which is suitable for airborne application is presented. The key techniques in terrain matching system realizing process including system workflow, terrain matching algorithm and selection criterion of matching region are expatiated. The experimental results prove the rationality and feasibility of the proposed solution.

SAR Image Coregistration Using Fringe Definition Detection

In order to overcome the limitation of cross correlation coregistration method for Synthetic Aperture Radar （SAR） interferometric pairs with low coherence, a new image coregistration algorithm based on Fringe Definition Detection （FDD） is presented in this paper. The Fourier transformation was utilized to obtain spectrum characteristics of interferometric fringes. The ratio between spectrum mean and peak was proposed as the evaluation index for identifying homologous pixels from interferometric images. The satellites ERS-1/2 C-band SAR acquisitions covering the Yangtze River plain delta, eastern China and ALOS/PALSAR L-band images over the Longmen Shan mountainous area, southwestern China were respectively employed in the experiment to validate the proposed coregistration method. The testing results suggested that the derived Digital Elevation Model （DEM） from FDD method had good agreement with that from the cross correlation method as well as the reference DEM at high coherence area. However, The FDD method achieved a totally improved topographic mapping accuracy by 24 percent in comparison to the cross correlation method. The FDD method also showed better robustness and achieved relatively higher performance for SAR image eoregistration in mountainous areas with low coherence.

A hybrid genetic algorithm for multi-modal image registration

This paper describes a new method for three-dimensional medical image registration. In the interactive image-guided HIFU （ High Intensity Focused Ultrasound） therapy system, a fast and precise localization of the tumor is very important. An automatic system is developed for registering pre-operative MR images with intra-operative ultrasound images based on the vessels visible in both of the modalities. When the MR and the ultrasound images are aligned, the eenterline points of the vessels in the MR image will align with bright intensities in the ultrasound image. The method applies an optimization strategy combining the genetic algorithm with the conjugated gradients algorithm to minimize the objective function. It provides a feasible way of determining the global solution and makes the method robust to local maximum and insensitive to initial position. Two experiments were designed to evaluate the method, and the results show that our method has better registration accuracy and convergence rate than the other two classic algorithms.

Fast uniform content-based satellite image registration using the scale-invariant feature transform descriptor

Content-based satellite image registration is a difficult issue in the fields of remote sensing and image processing. The difficulty is more significant in the case of matching multisource remote sensing images which suffer from illumination, rotation, and source differences. The scale-invariant feature transform （SIFT） algorithm has been used successfully in satellite image registration problems. Also, many researchers have applied a local SIFT descriptor to improve the image retrieval process. Despite its robustness, this algorithm has some difficulties with the quality and quantity of the extracted local feature points in multisource remote sensing. Furthermore, high dimensionality of the local features extracted by SIFT results in time-consuming computational processes alongside high storage requirements for saving the relevant information, which are important factors in content-based image retrieval （CBIR） applications. In this paper, a novel method is introduced to transform the local SIFT features to global features for multisource remote sensing. The quality and quantity of SIFT local features have been enhanced by applying contrast equalization on images in a pre-processing stage. Considering the local features of each image in the reference database as a separate class, linear discriminant analysis （LDA） is used to transform the local features to global features while reducing di- mensionality of the feature space. This will also significantly reduce the computational time and storage required. Applying the trained kernel on verification data and mapping them showed a successful retrieval rate of 91.67% for test feature points.

Polistes metricus queens exhibit personality variation and behavioral syndromes

Consistent differences in behavior between individuals, otherwise known as animal personalities, have become a staple in behavioral ecology due to their ability to explain a wide range of phenomena. Social organisms are especially serviceable to animal personality techniques because they can be used to explore behavioral variation at both the individual and group level. Despite the suc- cess of personality research in social organisms generally, and social Hymenoptera in particular, social wasps （Vespidae） have received little to no attention in the personality literature. In the pre- sent study, we test Polistes metricus （Vespidae; Polistinae） paper wasp queens for the presence of repeatable variation in, and correlations （＂behavioral syndromes＂） between, several commonly used personality metrics： boldness, aggressiveness, exploration, and activity. Our results indicate that P. metricus queens exhibit personalities for all measured traits and correlations between differ- ent behavioral measures. Given that paper wasps have served as a model organism for a wide range of phenomena such as kin selection, dominance hierarchies, mate choice, facial recognition, social parasitism, and chemical recognition, we hope that our results will motivate researchers to explore whether, or to what degree, queen personality is important in their research programs.