The realization of high-quality imaging under low sampling is an effective way to solve the practical application of ghost imaging. In this paper, we present an advanced framework of compressed ghost imaging under low sampling. During the imaging process, the regularization and mutual structure filtering operations are performed alternately, which we call mutual structure ghost imaging (MSGI). In the joint filtering of our proposed scheme, the mutual-structural information contained in both the reference image and the target one is applied to enhance the capability of important edge preserving. Thus, high-resolution ghost imaging results can be obtained under low sampling. Moreover, we have adopted a fast-converging iterative format to obtain better imaging results with fewer iterations. Simulation and experimental results show that the proposed method can achieve high-quality imaging results from the random speckle patterns under low sampling and promote the practical process of ghost imaging.

天然酯作为一种环保低碳液体电介质,被普遍认为是矿物油的良好替代品,但其在高场强、长间隙下的放电特性及绝缘性能尚不清晰.该文以天然酯绝缘油为研究对象,基于电流体动力学方程,考虑多种参与电离的甘油三酯分子的电离能、分子数密度和温度对载流子迁移率的影响,建立天然酯流注放电仿真模型,研究不同雷电冲击电压和放电间隙的流注发展特性及典型分子的电离情况,分析流注模式转换与甘油三酯分子电离的联系,以及油隙对击穿电压的影响.结果表明,天然酯的击穿特性不同于矿物油;流注模式转换与高电离能分子电离有关;间隙小于100 mm时,该模型有利于对雷电冲击电压与油隙关系进行模拟判断.该文可为研究天然酯流注发展特性提供新的思路和依据.

We report the evolution of the abundance, morphology, chemical species, and element fingerprints of magnetic particulate matter during its emission process in thermal power plants.

Recently gonadotropin releasing hormone (GnRH) and its agonistic analogs were demonstrated to have some direct actions in accessory reproductive organs. In our study the effects of GnRH and its analogs on some steroid hormone induced responses were investigated. GnRH and its analogs inhibited estradiol induced ornithine decarboxylase (ODC) and glucosamine-6-phosphate synthase activities in the uterus of rat. These enzymes which are markers for cell proliferation are regulatory enzymes in the biosynthetic pathways of polyamines and glycoproteins, respectively. Similarly, GnRH and its analogs also inhibited testosterone stimulated ODC activity in ventral prostate of rat. In addition, GnRH analog inhibited incorporation of radioactive precursors into RNA and protein induced by estradiol in uterus or dihydrotestosterone (DHT) in ventral prostate. In an effort to elucidate the mechanism of action of GnRH in uterus, it was found that GnRH analog treatment does not alter the estradiol receptor content in vivo. Also, GnRH does not show any effect on radioactive estradiol binding to its receptor in vitro. Hence, the inhibitory actions of GnRH in uterus may not involve estradiol receptors. However, GnRH analogs were found to have post-transcriptional effects. It was observed that DHT induced poly(A) polymerase activity in ventral prostate and estradiol induced poly(A) polymerase activity in uterus were inhibited by GnRH analog treatment. It was further observed that GnRH inhibited incorporation of [3H]uridine into poly(A)+ RNA of ventral prostate. This indicates that the inhibitory effects of GnRH involve post-transcriptional mechanisms.

To further increase combustion efficiency and reduce nitrogen oxide pollution caused by tannery wastes, three raw materials, including tannery sludge, chrome-tanned buffing dust, and chrome shavings, were burned together in a dual-bed model reactor under various conditions. In addition, a thermogravimetric analysis of co-combustion of three tannery wastes was studied in this study, which was conducive to understanding the combustion characteristics and positive effects. The comprehensive combustibility index S, the flammability index K r, and the stable combustion characteristic index G b all increased when the tannery sludge was blended with chrome-tanned buffing dust and chrome shavings, indicating that the combustion behavior was improved by co-combustion. For normal combustion, decreasing the gas volume flow and temperature resulted in a decrease in the oxidation of nitrogen compounds, consequently lowering the NO x emission. During air staged combustion, at an appropriate secondary gas ratio of about 10-40%, the NO x reduction would be increased from 10.9 to 19.3%. By increasing the tertiary gas volume flow from 0.2 to 1.1 L/min in decoupling combustion, an average relative NO x reduction efficiency of 47% was attained compared with normal combustion. The results offered a viable technology that resulted in a lower NO x emission and realized the application of decoupling combustion.

Non-blind image restoration is one of the most improtant research topics in the field of computer vision. It is also a typical ill-posed problem in mathematics. Its goal is to estimate a clear image from a blurred image when the point spread function is known. Its research focuses on how to make an appropriate compromise between improving clarity and suppressing noise. In the past 50 years, non-blind image restoration has made great progress. From the Wiener filtering to deep learning based methods, scholars have proposed hundreds of non-blind image restoration algorithms and applied them in various academic fields. This paper first introduces the basic concept and research significance of non-blind image restoration, then classifies and summarizes the main non-blind image restoration algorithms according to the algorithm attributes, which are generally divided into traditional methods and deep learning based methods. The traditional methods are divided into the direct method and iterative method, then are analyzed for their advantages and disadvantages. The performance of representative restoration algorithms is compared in a varity of typical experiments. Finally, the development trend and important research directions of non-blind image restoration algorithms are proposed.

Red mud (RM) with the high alkalinity as a catalyst was evaluated for coal pyrolysis in a fixed bed as well as CO2 gasification of its resultant char in a thermogravimetric analyzer (TGA). The addition of RM into coal could improve the quality of tar during pyrolysis and enhance the reactivity of char during gasification. For catalytic pyrolysis with 12 wt% RM at 600 °C, the light fraction in tar was 72.0 wt%, which increased by 20.0%, compared with coal pyrolysis alone. The role of metal oxides in RM on coal pyrolysis was further clarified as well. After catalytic pyrolysis with RM, the specific surface area of resultant char increased, especially for mesoporous surface area, and meanwhile the sodium in RM was proved to migrate to the char surface. These positive factors contributed to the CO2 gasification activity of char. RM with the high alkalinity showed a promising catalyst candidate for coal pyrolysis and gasification in terms of its catalytic effects and low cost.

With the building of sustainable cities being listed as one of the Sustainable Development Goals in the 2030 Agenda, cities in developing countries are facing more severe challenges. Therefore, it has become very urgent to evaluate and compare sustainability under different policy intervention scenarios. Based on the principle of system dynamics, this study constructed an urban sustainability evaluation model covering six subsystems: economy, livelihood, risk, environment, pollution governance, and resource. Using 13 cities in the Beijing Tianjin-Hebei region as study cases, 5 future policy scenarios were designed under the framework of the Shared Socioeconomic Pathways to simulate the variation of the urban sustainability index in each city by 2035. The results reveal that: (1) Medium and small-sized cities around Beijing are facing more challenges to achieve sustainable urban development; (2) the urban sustainability index in each city varies under different policy scenarios. (3) the gap of urban sustainability in the Beijing-Tianjin-Hebei region does not show a significant narrowing trend and is likely to widen in the future. The approach can also be applied to other regions to provide decision support for choosing urban development pathways after comparing possible future trajectories of sustainable urban development.

As a sub-topic in computational imaging, simple lenses imaging provides an alternative way to achieve a close-to-perfect imaging system design, which simplifies the complex, multiple lens elements optical system to one simple lenses, and delivers the aberration correction process to a dedicated reconstruction algorithm. In this paper, we propose an effective blind restoration algorithm for optical aberrations removal without calibrate procedure. In general, our algorithm consists of two steps: a blind non-uniform PSFs estimation and a non-blind reconstruction. The algorithm can be directly used for simple lenses imaging system, and further utilized for aberrations removal cases in traditional optical imaging equipment. We obtain results that are comparative with the pre-calibrate non-blind restoration.

The quality and freshness of vegetables not only affect the taste, but the nutrient content. The research on detection of chlorophyll and water content that are important reference indexes of vegetables quality and freshness has become more attention to the researchers both at home and abroad. With the quickness, high efficiency, non-destruction and non-contact features, the novel visible/near-infrared spectral analysis technology is more suitable for real-time detection of vegetables, comparing wtih traditional estimating methods by naked eyes. The relevant research is primarily focus on retrieval of growing vegetation chlorophyll and water content at present. There is little research aiming at ripe vegetables in market, or lacking of universality because of single species. Moreover, collecting of spectral data requires professional Field Spectrometer, wasting time and energy. There is a distance between research of physiological and biochemical index and practical application. In order to combining the research with the real life, this paper builds quickly, precise, universal models that can retrieve chlorophyll and water content in vegetables, based on Smart Cellphone Spectral System(SCSS). Simultaneously, SVC are used to validate the reliability of SCSS. Five kinds of common vegetables (spinach, rape, romaine, lettuce and baby cabbage) are selected as samples in experiment, and the ways of cold storage and normal temperature preservation are used to simulate the market and supermarket environment. Datas are collected per 24 hours. Then Band-Selecting and Wavelet-Transform preprocessing are adopted to improve the quality of spectral data. This paper constructs Vegetable Chlorophyll Retrieval Index ( VCRI) and Vegetable Water Retrieval Index (VWRI) , and extracts the correlation coefficients between the two indexes and measured values of chlorophyll and water content as weight coefficients. Finally, the chlorophyll and water content retrieval models are built. The result shows, SVC and SCSS have the same sensitive bands to chlorophyll and water content. The sensitive wavelength for chlorophyll retrieval is from 730 to 980 nm. The precision R-2 are 0. 863 and 0. 8081, and standard deviation are 8. 679 5 and 8. 892 5 respectively. The sensitive wavelength for water content retrieval is from 950 to 1 000 nm. The precision R-2 are 0. 742 9 and 0. 712 9, and standard deviation are 8. 789 9% and 8. 861 4% respectively. The result of SVC and SCSS is similar enough to prove the validation of new-style Smart Cellphone Spectral System. Furthermore, SCSS has the advantage of small size and low price. It can smartly detect the quality and freshness index of vegetables, with the features of internet cloud services and data feedback in real-time. This makes the spectral analysis technology applying to the people's daily life.

In the applications of scientific imaging and space exploration, the dynamic range of imaging systems is usually required to reach more than 120 dB. In order to observe a highly dynamic scene in real time, we designed an imaging system based on a digital micromirror device (DMD) that is used as a spatial light modulator. First, we designed a binocular highly dynamic light-adjusting system based on a DMD according to the DMD's optical structure. Second, in order to realize the registration between the micromirrors of a DMD and pixels of the two cameras, a pixel-matching algorithm was developed. Finally, we introduce a novel light-adjusting algorithm that can recover the highly dynamic data of the dynamic scene. Experiments showed that the deviation between the DMD and the two cameras is reduced to 0.48 pixels after correction, and that bright and dark targets in a high-dynamic-range scene can both be displayed simultaneously in one image with high quality after light adjustment. The dynamic range of the system is theoretically 209 dB, which meets the requirements of high-dynamic-range observation.

遥感,顾名思义,就是遥远地感知对象,是一种不接触物体而感知和观测物体并测量、分析和判定该物体或目标的性质、空间展布、类型和数量的感知技术.我们这里所讲的遥感技术主要指通过一定的观测平台,如卫星、飞机、无人机等,从空中或空间观测或感知我们居住并赖以生存的地球.

Magnetic resonance imaging (MRI) reconstruction from the smallest possible set of Fourier samples has been a difficult problem in medical imaging field. In our paper, we present a new approach based on a guided filter for efficient MRI recovery algorithm. The guided filter is an edge-preserving smoothing operator and has better behaviors near edges than the bilateral filter. Our reconstruction method is consist of two steps. First, we propose two cost functions which could be computed efficiently and thus obtain two different images. Second, the guided filter is used with these two obtained images for efficient edge-preserving filtering, and one image is used as the guidance image, the other one is used as a filtered image in the guided filter. In our reconstruction algorithm, we can obtain more details by introducing guided filter. We compare our reconstruction algorithm with some competitive MRI reconstruction techniques in terms of PSNR and visual quality. Simulation results are given to show the performance of our new method.

Since hyperspectral remote sensing (HRS) came in the middle 1980s, a number of hyperspectral imagers (e.g., EO-1 Hyperion) have been developed all over the world. China, as one of the pioneers in HRS technology development, also has been active and contributed significantly to the HRS community. This paper updates recent advances and future plans in Chinese developments in spaceborne imaging spectroscopy. Particularly, two powerful civilian micro/nano-hyperspectral mini-satellites (Spark01 and Spark02) as well as China's first Carbon monitoring satellite (called TanSat), all newly launched at the end of 2016 were introduced.

Diagnostic absorption features can indicate the existence of specific materials,which is the foundation of mineral analysis with optical remote sensing data .In hyperspectral data processing, the most commonly used method to extract absorption feature, is Continuum Removal (CR) .As for multispectral data, Principle Component Analysis and other indirect methods were used to extract absorption information, and little research has been done on full-band absorption feature extraction .Classification of similar minerals is one of the major difficulties in mineral spectral analysis, while there is no valid index for spectral difference between similar mineral groups .Absorption feature extraction may improve the classification accuracy, but there is no research to investigate the impact of absorption feature extraction on spectral difference between similar mineral s .This paper summarized the principle of mineral spectral difference, and proposed the concept of Class Separability Ratio (CSR), which was verified to be a valid index for spectral difference between similar mineral categories .Thro ugh comparison experiments on alunite and kaolinite spectra, including USGS sp ectral library spectra and resampled spectra in accordance with the band setting s of HYPERION, ASTER and OLI, the impact of absorption feature extraction on spectral difference between similar minerals were investigated .Experimental results show that valid absorption feature extraction can greatly enhance the spectral difference between similar minerals, and the spectral difference is positively correlated with spectral resolution .Besides, the results of CR can be severely affected by spectral resolution and band center positions, and the absorption feature spectra extraction results for multispectral datasets need to be improved .This research laid the foundation of precise identification between similar mineral categories, and provided valuable reference for the band settings of future geology remote sensing sensors .

An increasingly common requirement in remote sensing is the integration of hyperspectral data collected simultaneously from different sensors (and fore-optics) operating across different wavelength ranges. Data from one module are often relied on to correct information in the other, such as aerosol optical thickness (AOT) and columnar water vapor (CWV). This paper describes problems associated with this process and recommends an improved strategy for processing remote sensing data, collected from both visible to near-infrared and shortwave infrared modules, to retrieve accurate AOT, CWV, and surface reflectance values. This strategy includes a workflow for radiometric and spatial cross-calibration and a method to retrieve atmospheric parameters and surface reflectance based on a radiative transfer function. This method was tested using data collected with the Compact Airborne Spectrographic Imager (CASI) and SWIR Airborne Spectrographic Imager (SASI) from a site in Huailai County, Hebei Province, China. Various methods for retrieving AOT and CWV specific to this region were assessed. The results showed that retrieving AOT from the remote sensing data required establishing empirical relationships between 465.6 nm/659 nm and 2105 nm, augmented by ground-based reflectance validation data, and minimizing the merit function based on AOT@550 nm optimization. The paper also extends the second-order difference algorithm (SODA) method using Powell's methods to optimize CWV retrieval. The resulting CWV image has fewer residual surface features compared with the standard methods. The derived remote sensing surface reflectance correlated significantly with the ground spectra of comparable vegetation, cement road and soil targets. Therefore, the method proposed in this paper is reliable enough for integrated atmospheric correction and surface reflectance retrieval from hyperspectral remote sensing data. This study provides a good reference for surface reflectance inversion that lacks synchronized atmospheric parameters.

Phyllosilicate belongs to hydrated silica,which is a principal form of hydrous minerals on the martian surface.It’s al-so an indicator in comparing different sediments and degree of aqueous alteration.Therefore,it’s essential to establish its recog-nition model for studying the geologic evolution of the Mars.Short-wave infrared (SWIR)spectral bands and thermal infrared (TIR)spectral bands have distinct spectral response to the mineral groups and ions,so they have distinctive advantages in detec-ting minerals.However the method of combining SWIR and TIR to recognize phyllosilicate is rarely studied.Based on the USGS spectral library,facing Compact Reconnaissance Imaging Spectrometer for Mars(CRISM)and Thermal Emission Imaging Sys-tem(THEMIS),we conducted the research on the mechanism of the spectral response of phyllosilicate,and established the SWIR and TIR identification model respectively,then combined the SWIR and TIR spectral features to build the combined recognition model of phyllosilicate with Fisher discriminant analysis.The results of cross validation show that the identification accuracy of combined model is the highest,which can correctly classify 90.6% of the mineral samples and improve the identification preci-sion of phyllosilicate effectively.

Diagnostic absorption feature has the potential to be the key factor in the mineral information extraction from vegetation-covered area. Reference Spectral Background Removal (RSBR) could simulate the background curve based on the reference spectral background, and eliminate the influence through the background removal process. In this paper, RSBR was introduced into to mineral absorption feature extraction from high vegetation density area. Experiments on simulated data validated its great potential in mineral exploration in vegetation-covered area.

Basing on the Aerosol Product data from the AERONET website, We analyzed the 550nm aerosol optical depth(AOD), Angstrom exponent(AE), aerosol volume concentration and aerosol size distribution from 2003 to 2013, excluding the year 2008 due to lacking of data. The research shows: high AOD often occurred in spring and summer. The coarse particle such as dust particle dominates in the spring and the fine particle dominates in the summer. On the interannual variation, there is an obvious trend: From 2003 to 2007, the AOD was often above 1.5 due to the dust pollution from north areas in spring and took the second place in summer. Before and after the Beijing Olympic Games, the atmospheric condition improved. Nevertheless, the AOD rised again till 2012 and 2013. In addition, fine mode aerosol optical depth is closed concerned with PM2.5 and the fine particle volume concentration affects the AOD more. In a word, the study of aerosol changing rule in Beijing from 2003 to 2013 can reflect some environment issues and contribute to atmospheric improvement as a related reference.

In this work, we propose a new approach for efficient edge-preserving image deconvolution. Our algorithm is based on a novel type of explicit image filter - guided filter. The guided filter can be used as an edge-preserving smoothing operator like the popular bilateral filter, but has better behaviors near edges. We propose an efficient iterative algorithm with the decouple of deblurring and denoising steps in the restoration process. In deblurring step, we proposed two cost function which could be computed with fast Fourier transform efficiently. The solution of the first one is used as the guidance image, and another solution will be filtered in next step. In the denoising step, the guided filter is used with the two obtained images for efficient edge-preserving filtering. Furthermore, we derive a simple and effective method to automatically adjust the regularization parameter at each iteration. We compare our deconvolution algorithm with many competitive deconvolution techniques in terms of ISNR and visual quality.