海洋二号卫星扫描辐射计海洋参数反演算法研究

针对海洋二号(HY-2)卫星扫描辐射计,利用辐射传射方程模拟,建立了海面温度、海面风速、大气水汽含量、大气液态水含量和雨率的反演算法,并利用扫描辐射计在轨数据对上述参数进行反演。经过对反演的海面温度和风速全球产品的真实性检验表明,算法合理可行,能够反演大气海洋参数,反演精度满足设计指标需求。目前,其他参数的反演产品的检验还在进行,而且反演算法还要根据对辐射计测量值定标的深入而进一步优化。     

地表温度的卫星遥感

研究了地表温度卫星遥感测量中的两个关键因子——大气修正和发射率效应.正确选择了经仿真计算分析求得的地面温度的反演算法,对我国戈壁地区地表温度进行了卫星资料的反演.通过与地面测量的比较证实了反演算法的可靠性.为了提高卫星反演地表温度的精度,本研究提出了自然地物发射率方向特性的重要性,对特定地物作了发射率角度变化的测量,在实际地表温度反演中作出了恰当的修正,改善了反演精度.     

A mono-window algorithm for retrieving sea surface temperatures by using mid-infrared data

基于中红外波段受大气水汽影响小的特点,从大气辐射传输的角度,提出了利用中红外数据反演海表温度的单通道算法.该算法适用于单通道的中红外数据,时空变化适应性强,对大气温湿廓线等辅助信息的精度要求较低.为了验证该算法的可行性和准确性,将此算法反演的海表温度产品与美国国家数据浮标中心提供的浮标数据及MODISSST标准产品进行了比对验证.结果表明,此单通道算法反演的海表温度达到了较高的精度,能够满足海洋锋面、上升流、海洋涡旋等短周期海洋现象的观测需求.     

利用AMSR-E被动微波数据反演地表温度的神经网络算法

结合对地观测卫星AQUA多传感器/多分辨率的特点,研究了利用AMSR-E被动微波数据反演地表温度的神经网络算法.MODIS地表温度(LST)产品被作为地表温度实测数据,对应的平均温度被用作对应AMSR-E像元的实际地表温度,从而克服由于AMSR-E像元尺度太大和云的影响而难以获得地表实测数据的难点.反演结果分析表明,利用神经网络能够精确地由AMSR-E数据反演地表温度.当使用5个频率10个通道反演时,反演精度最高,说明使用更多的通道能更好地消除土壤水分、粗糙度、大气和其它因素的影响.相对于MODIS温度产品,用此算法反演的平均误差约低于2K.     

辽宁地区陆面实测温度与MODIS反演产品对比分析

陆面温度（LST）是区域和全球尺度地表物理过程中的一个关键因子,亦是研究地表和大气之间物质交换和能量交换的重要参数。因精确反演LST具有一定的难度,因此反演LST成为当今研究的热点之一。气象卫星为快速获取大范围辐射面瞬时温度提供了重要手段,本文基于MODIS数据2、19波段反演水汽含量,31、32波段和推广的分裂窗算法反演辽宁地区陆面温度。通过对辽宁地区地而观测站实测温度的对比,表明反演精度与实测数据相差不大,具有实际参考价值。     

地表温度的卫星遥感

研究了地表温度卫星遥感测量中的两个关键因子－大气修正和发射率效应。正确选择了经仿真计算分析求得的地面温度的反演算法,对我国戈壁地区地表进行了卫星资料的反演。通过与地面的比较证实了反演算法的可靠性。为了提高筢演地表的精度,本研究提出了自然地物发射率方向特性的重要性,对特定地物作了发射率角度变化的测量,在实际地表温度反演中作出了恰当的修正,改善了反演精度。     

基于遗传算法的混凝土-维瞬态导热反问题

基于Laplace积分变换法和遗传算法，提出了一种混凝土-维瞬态导热反问题求解的新方法。运用Laplace变换将温度的求解表示为只与空间坐标及浇筑时间有关的函数，使得反问题的求解具有测点布置灵活的特点。运用遗传算法寻求非线性反演问题全局最优解，只需要若干点温度实测值便可实现多个热学参数的同时反演，算例对反演方法的反演精度及数值稳定性给出了满意的证明。     

L/S波段微波遥感海水盐度和温度的反演算法

对基于多元线性回归构造的非线性多项式形式的L/S双波段微波遥感海水盐度和温度反演算法进行了误差分析,并优化了多项式的系数.进一步提出了一种半解析的反演算法,该算法基于海面微波发射理论模型,构建包含盐度和温度两个反演目标的二元非线性方程组,利用数值解法直接求解该方程组,以反演盐度和温度.该反演算法较以往的算法具有更高的反演精度.     

利用嫦娥一号卫星微波探测仪数据反演月球表面物理温度

本文利用理论研究的结果,建立了月表物理温度反演模型,结合嫦娥一号微波探测仪(CELMS)数据对全月球物理温度进行了反演。同时分析了物理温度变化对微波辐射的影响及其与表面地形等的关系,为其他月表信息反演提供了依据和物理温度的测量信息。     

16Cr2Ni2A钢连续冷却转变图及等温转变图的测定

在Ｆｏｒｍａｓｔｏｒ－Ｄ型全自动快速膨胀仪对１６Ｃｒ２Ｎｉ２Ａ钢的ＣＣＴ和ＴＴＴ曲线进行测试，研究了不同温度，冷却速度下该钢的金相组织和相变特点，建立了一套完整的ＣＣＴ和ＴＴＴ图。     

Limited-angle computed tomography for sandwich structures using data fusion

Both conventional and limited-angle computed-tomography (CT) are ill-posed problems, but where conventional CT has a small null space with few dimensions, limited-angle CT has a much larger null space and is severely ill-posed. The nature of the ill-posedness of limited-angle CT dictates that any limited-angle reconstruction method must interpolate from partial data in the Fourier domain. Large aluminum-core sandwich structures, such as those of aircraft control surfaces, simultaneously prevent full range data acquisition for CT and have face sheets that lie primarily in the limited-angle Radon transform null space. Consequently, interpolation of missing data is not possible and limited-angle CT for large sandwich structures is not feasible. This paper presents a novel method for limited-angle CT that addresses this problem. The method uses constraint-based data fusion to reduce the null space of the problem in a manner consistent with the specimen. Measurements of spatial support and face sheet thickness provide data for the additional constraints. By using the method, accurate reconstruction of sandwich structures becomes possible, where it would otherwise be impossible. The method of convex projections solves the inverse problem posed by the fusion system well because it is fast (for this problem) and easily incorporates the fusion constraints. Experimental results based on synthetic data show the improvement in reconstruction accuracy obtained by the fusion method. Real data results show the successful application of the method to a plexiglass phantom.     

Distance measures for medical image retrieval

Imaging has occupied a huge role in the management of patients, whether hospitalized or not. Depending on the patient's clinical problem, a variety of imaging modalities were available for use. Radiology is the branch of medical science dealing with medical imaging. It may use X‐ray machines or other such radiation devices. It also uses techniques that do not involve radiation, such as magnetic resonance imaging (MRI) and ultrasound (US). Commonly used imaging modalities include plain radiography, computed tomography (CT), MRI, US, and nuclear imaging techniques. Each of these modalities has strengths and limitations which dictates its use in diagnosis. The usage of modality for a particular problem must be reviewed with emphasis on method of generating an image with costs, strengths and weaknesses, and associated risks. The reason for image retrieval is due to increase in acquisition of images. Physicians and radiologists feel better while using retrieval techniques for faster remedy in surgery and medicine due to the following reasons: giving details to the patients, searching the present and past records from the larger databases, and giving solutions to them in a faster and more accurate way. Similarity measures are one of the techniques that help us in retrieval of medical images. Similarity measures also termed as distance metrics, which plays an important role in CBIR and CBMIR. They calculate the visual similarities between the query image and images in the database which were ranked by their similarities with the query image. Different similarity measures have different effects in an image retrieval system significantly. So, it is important to find the best distance metrics for CBIR system. In this article, various distance methods were used and then they are compared for effective medical image retrieval. A double‐step approach is followed for effective retrieval. This article describes some easily computable distance measures for medical image retrieval using measures such as probability, mean, standard deviation, skew, energy, and entropy. The distance measures used are Euclidean, Manhattan, Mahalanobis, Canberra, Bray‐Curtis, squared chord, and Squared chi‐squared. Two kind of decision rules precision and accuracy were used for measuring retrieval. A dataset is created using various imaging modalities like CT, MRI, and US images. From the final results, it is very clear that each distance metric with each measures shows different results in retrieval of medical images. It is found that the distance metrics with all the measures shows different precision and recall value calculated from their retrieved medical images. The best retrieval results for Euclidean distance metric is only with probability measure showing 75% of precision and 30% of recall when comparing with other measures. The best retrieval results for Manhattan distance metric is only with mean as a measure giving 50% of precision and 20% of recall when compared its performance with other measures in the retrieval of medical images. The best retrieval results for Mahalanobis distance metric is only with probability as a measure giving 75% of precision and 30% of recall when compared its performance with other measures in the retrieval of medical images. The best retrieval results for Canberra distance metric is only with mean as a measure giving 50% of precision and 20% of recall when compared its performance with other measures in the retrieval of medical images. The best retrieval results for Bray‐Curtis distance metric is only with mean as a measure giving 50% of precision and 20% of recall when compared its performance with other measures in the retrieval of medical images. The best retrieval results for squared‐chord distance metric is only with mean as a measure giving 50% of precision and 20% of recall when compared its performance with other measures in the retrieval of medical images. The best retrieval results for squared chi‐chord distance metric is only with mean as a measure showing 50% of precision and 20% of recall when compared its performance with other measures in the retrieval of medical images. These results indicate that these easily computable similarity distance measures have a wide variety of medical image retrieval applications. © 2013 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 23, 9–21, 2013     

Fuzzy-HLSTM (Hierarchical Long Short-Term Memory) for Agricultural Based Information Mining

This research proposes a machine learning approach using fuzzy logic to build an information retrieval system for the next crop rotation. In case-based reasoning systems, case representation is critical, and thus, researchers have thoroughly investigated textual, attribute-value pair, and ontological representations. As big databases result in slow case retrieval, this research suggests a fast case retrieval strategy based on an associated representation, so that, cases are interrelated in both either similar or dissimilar cases. As soon as a new case is recorded, it is compared to prior data to find a relative match. The proposed method is worked on the number of cases and retrieval accuracy between the related case representation and conventional approaches. Hierarchical Long Short-Term Memory (HLSTM) is used to evaluate the efficiency, similarity of the models, and fuzzy rules are applied to predict the environmental condition and soil quality during a particular time of the year. Based on the results, the proposed approaches allows for rapid case retrieval with high accuracy.     

Optical sparse aperture imaging

The resolution of a conventional diffraction-limited imaging system is proportional to its pupil diameter. A primary goal of sparse aperture imaging is to enhance resolution while minimizing the total light collection area; the latter being desirable, in part, because of the cost of large, monolithic apertures. Performance metrics are defined and used to evaluate several sparse aperture arrays constructed from multiple, identical, circular subapertures. Subaperture piston and/or tilt effects on image quality are also considered. We selected arrays with compact nonredundant autocorrelations first described by Golay. We vary both the number of subapertures and their relative spacings to arrive at an optimized array. We report the results of an experiment in which we synthesized an image from multiple subaperture pupil fields by masking a large lens with a Golay array. For this experiment we imaged a slant edge feature of an ISO12233 resolution target in order to measure the modulation transfer function. We note the contrast reduction inherent in images formed through sparse aperture arrays and demonstrate the use of a Wiener-Helstrom filter to restore contrast in our experimental images. Finally, we describe a method to synthesize images from multiple subaperture focal plane intensity images using a phase retrieval algorithm to obtain estimates of subaperture pupil fields. Experimental results from synthesizing an image of a point object from multiple subaperture images are presented, and weaknesses of the phase retrieval method for this application are discussed.     

Generalized eikonal approximation for fast retrieval of particle size distribution in spectral extinction technique

In retrieving particle size distribution from spectral extinction data, a critical issue is the calculation of extinction efficiency, which affects the accuracy and rapidity of the whole retrieval. The generalized eikonal approximation (GEA) method, used as an alternative to the rigorous Mie theory, is introduced for retrieval of the unparameterized shape-independent particle size distribution (PSD). To compute the extinction efficiency more efficiently, the combination of GEA method and Mie theory is adopted in this paper, which not only extends the applicable range of the approximation method but also improves the speed of the whole retrieval. Within the framework of the combined approximation method, the accuracy and limitations of the retrieval are investigated. Moreover, the retrieval time and memory requirement are also discussed. Both simulations and experimental results show that the combined approximation method can be successfully applied to retrieval of PSD when the refractive index is within the validity range. The retrieval results we present demonstrate the high reliability and stability of the method. By using this method, we find the complexity and computation time of the retrieval are significantly reduced and the memory resources can also be saved effectively, thus making this method more suitable for online particle sizing.     

基于小波系数邻域特征的CT与MR图像融合方法

提出一种基于小波变换的像素级CT,MR医学图像融合方法,利用离散小波变换分别将两幅源图像进行多尺度分解,再用不同的小波系数邻域特征指导高频分量和低频分量的小波系数的融合,低频分量采用邻域方差指导,高频分量采用邻域能量指导,最后根据融合图像的各小波系数重构融合图像.实验表明:不论从主观感受,还是采用信息熵和平均梯度两项指标作为客观定量评价标准,该方法都优于传统的融合方法,获得的融合图像有效地综合了CT与MR图像信息,能够同时清晰地显示脑部骨组织和软组织.     

旋转不变纹理特征用于两级图像检索

针对图像中常见的旋转问题提出一种旋转不变纹理特征进行两级图像检索的方法。粗检中,通过坐标变换把图像的旋转转换为行移,并提取近似行移不变的小波特征,结合粗比较算法对整个图像库进行粗检。然后对通过粗检的图像进行 Gabor 变换,提取旋转不变精检索特征,并使用Canberra 距离进行相似性度量。通过对旋转图像库的测试表明,该方法不仅加快了运算速度,且当参数选择适当时,在相同特征条件下,检索率比直接使用精检索方法检索时还提高了 1.625%。     

基于结构相似性的轴类零件加工特征可拓关联方法

在现有轴类零件相似性检索方法的基础上,将轴类零件的信息模型划分为结构特征层和加工工艺层,并利用可拓基元方法进行形式化描述.提出从轴类零件结构和加工工艺两方面进行相似性检索的方法:首先基于结构矩阵表达方法,对轴类零件的结构特征进行相似性检索,从实例库中检索出2~5个相似实例,然后以可拓综合关联函数进行加工特征的相似度匹配,得出与新零件最相似的零件.通过实例验证,该方法具有可行性,并且可在检索过程中动态调整系数水平,具有检索适应性强的优点.