鄱阳湖高浑浊水体悬浮颗粒物粒径分布及其对遥感反演的影响

悬浮颗粒物粒径分布特征为水环境结构与功能研究提供了重要信息,但目前针对内陆湖泊的研究还很少。依据2008年—2011年鄱阳湖丰枯水期实测数据,对悬浮颗粒物粒径分布的时空特征及光学特性进行了研究。鄱阳湖悬浮颗粒物粒径具有季节性变化特点：枯水期南部湖区颗粒物粒径大于北部湖区,而丰水期南北部湖区差异不大。同时,悬浮颗粒物粒径分布对水体吸收系数、衰减系数和散射系数都有影响。鄱阳湖水体总颗粒物吸收系数北部观测值高于南部;颗粒物中值粒径与总颗粒物比吸收系数呈负相关关系,这可能是由浑浊水体中存在的矿物颗粒物打包效应引起。鄱阳湖水体总颗粒物衰减系数和散射系数的时空分布规律相似：枯水期具有明显的区域性差异而丰水期区域性差异不大。遥感反射率、总颗粒物散射系数光谱斜率以及颗粒物粒径分布斜率之间的函数关系为遥感反射率表征粒径分布情况以及定量分析悬浮颗粒物粒径分布特征对遥感反射率的影响提供了依据。悬浮颗粒物粒径分布、颗粒物后向散射概率与颗粒物复折射率密切相关,可以反映鄱阳湖水体悬浮颗粒物组分信息。     

前向迭代多随机相位光学图像加密方法的研究

基于光学4f级联系统,采用前向迭代算法和通过产生多个随机相位板对图像进行了加密和解密。给出了该方法的原理和迭代实现的过程。对该方法在收敛速度、解密图像质量、相位板数目和相位量化阶数对解密图像质量的影响以及保密和安全性能等方面进行了分析和研究。模拟结果表明,该方法收敛速度快,解密图像质量好,可以降低相位板相位量化阶数有限所引起的误差对解密图像质量的影响,图像的安全和保密性能也得到了很大的提高。     

相位恢复算法用于光学面形检测的实验研究

 针对相位恢复测量中遇到的初始相位估计、传播因子和收敛判断等问题,以柱面透镜的光学面形为恢复对象,应用迭代相位恢复算法完成了对柱面透镜的光波波前的相位恢复实验,并对实验结果进行了分析。实验结果表明：根据被测对象的光波形态选择最接近的初始相位能够加快收敛速度,避免局部收敛,是保证结果准确与可靠的重要条件。通过对两个记录面上的光强之和做求比值运算计算传播因子 ,并应用到传播公式中,能够消除激光光束本身稳定性与探测器响应均匀性等因素对计算结果的影响。     

Securing color image by using phase-only encoding in Fresnel domains

We propose a novel color image hiding scheme with three channels of cascaded Fresnel domain phase-only filtering. The original color image is encoded into three phase masks by using the Gerchberg–Saxton iterative phase retrieval algorithm with another predefined phase key. The individual phase masks are placed in the inputs of the Fresnel domains of the red–green–blue channels and the phase key in the public channel, during the optical retrieval. The physical parameters in the optical system will be regarded as the additional keys for security enhancement. Numerical simulation is performed to test the validity of our scheme.     

GS方法恢复低频相位噪声

 将Gerchberg-Saxton(GS)反演方法应用于恢复高功率激光装置的低频相位噪声研究中,通过数值模拟计算,给出了很好的迭代结果。为设计合理的相位板提供了依据。同时也为光束诊断系统提供了一种测量相位的方法。     

Solving inverse scattering problems in biological samples by quantitative phase imaging

Quantitative phase imaging (QPI), a method that precisely recovers the wavefront of an electromagnetic field scattered by a transparent, weakly scattering object, is a rapidly growing field of study. By solving the inverse scattering problem, the structure of the scattering object can be reconstructed from QPI data. In the past decade, 3D optical tomographic reconstruction methods based on QPI techniques to solve inverse scattering problems have made significant progress. In this review, we highlight a number of these advances and developments. In particular, we cover in depth Fourier transform light scattering (FTLS), optical diffraction tomography (ODT), and white‐light diffraction tomography (WDT).

     

Phase retrieval in optical fiber modal interference for structural health monitoring

A method based on data dependent system (DDS) for extraction of phase in fiber modal interference is presented. The interference patterns of LP₀₁ & LP₁₁, LP₀₁ & LP₀₂ and LP₀₆ &LP₀₇ within the fiber have been recorded under different launching conditions. The patterns were characterized by means of autoregressive model and the self coherence functions of the corresponding interferogram were determined. It would provide the phase distribution of the pattern and the modulation of group delay due to the measurand. An application has been made for measuring strain in a simply supported beam under different loading conditions. Results are presented for the applied strain in the range of 270-1500 μ strain.     

An evaluation of infrared microwindows for ozone retrievals using the Eureka Bruker 125HR Fourier transform spectrometer

A Bruker 125HR Fourier transform spectrometer was installed at the Polar Environment Atmospheric Research Laboratory (PEARL) at Eureka, Nunavut, Canada in the summer of 2006 to study atmospheric composition. Using the optimal estimation method, typically over a limited spectral region called a microwindow, information about the vertical distribution of trace gas species that have absorption bands in the mid-infrared spectral range can be retrieved. Total and partial columns can also be determined to show the temporal evolution of the target gas. For ozone in particular, retrievals have been performed using several of its many mid-infrared absorption features, resulting in a lack of consistency in the literature in the microwindows chosen for retrievals. This work focuses on the optimization of the ozone retrieval, assessing a set of 22 microwindows between 780 and 3052 cm⁻¹ to determine which is best suited to conditions at Eureka. The 1000-1004.5 cm⁻¹ spectral interval is shown to be the most sensitive to both the stratosphere and troposphere. This microwindow gives the highest number of degrees of freedom for signal (∼7 for total column), and the smallest total error (4.3%) compared with 21 other spectral regions. Retrievals performed with this microwindow agree well with results obtained from other instruments on-site. Total column ozone measured by the Bruker 125HR in this microwindow agreed to 2% with two other Fourier transform spectrometers, to 0.7% with a Brewer spectrophotometer, to 8% with a SAOZ UV-VIS spectrometer, and to 7% with ozone sondes.     

Content-based image retrieval using visually significant point features

This paper presents a new image retrieval scheme using visually significant point features. The clusters of points around significant curvature regions (high, medium, and weak type) are extracted using a fuzzy set theoretic approach. Some invariant color features are computed from these points to evaluate the similarity between images. A set of relevant and non-redundant features is selected using the mutual information based minimum redundancy-maximum relevance framework. The relative importance of each feature is evaluated using a fuzzy entropy based measure, which is computed from the sets of retrieved images marked relevant and irrelevant by the users. The performance of the system is evaluated using different sets of examples from a general purpose image database. The robustness of the system is also shown when the images undergo different transformations.     

A statistical approach to crosslingual natural language tasks

The existence of huge volumes of documents written in multiple languages on Internet leads to investigate novel algorithmic approaches to deal with information of this kind. However, most crosslingual natural language processing (NLP) tasks consider a decoupled approach in which monolingual NLP techniques are applied along with an independent translation process. This two-step approach is too sensitive to translation errors, and in general to the accumulative effect of errors. To solve this problem, we propose to use a direct probabilistic crosslingual NLP system which integrates both steps, translation and the specific NLP task, into a single one. In order to perform this integrated approach to crosslingual tasks, we propose to use the statistical IBM 1 word alignment model (M1). The M1 model may show a non-monotonic behaviour when aligning words from a sentence in a source language to words from another sentence in a different, target language. This is the case of languages with different word order. In English, for instance, adjectives appear before nouns, whereas in Spanish it is exactly the opposite. The successful experimental results reported in three different tasks - text classification, information retrieval and plagiarism analysis - highlight the benefits of the statistical integrated approach proposed in this work.