基于图像的光照模型的研究与实现

为了把计算机生成的虚拟物体更好地融入真实场景的实拍照片中,实现光照一致性的效果,提出了一个基于图像的光照模型,它使用光测图作为光源从而实现对场景的照明。在研究基于图像的局部光照模型时,又提出了双向折射率分布函数这一概念,从而简化了局部光照模型的设计。在实现阶段,采用立方体环境映照来表示场景,采用光测图记录环境映照中光辐射的分布信息,从而提高了绘制效率。实验表明,本模型较成功地实现了光照一致性,在增强现实、图像合成等方面具有很大的应用价值。

倾斜摄影测量技术在永靖光伏测图中的应用

传统的分布式光伏测图通过载波相位差分技术进行实地采集数据,集中式光伏具有体量大、地形复杂、设计周期短等突出特点,采用传统勘测手段测图费时费力,且在时间节点难以满足业主要求,在永靖光伏测图过程中采用无人机倾斜摄影技术生成测区的实景三维模型,在实景三维模型上三维测绘大比例测图地形图,随机选取检查点进行精度验证,其结果满足1:1000比例测图精度要求。

能抑制不均匀照明光影响的分块二值化

针对散斑干涉条纹的特点，提出了一种能抑制不均匀照明光影响的二值化方法——分块二值法，此算法通过人机交互，能更好地分割物体．

Numerical Simulation and Analysis of Bipolar Junction Photogate Transistor for CMOS Image Sensor

A new photodetector--bipolar junction photogate transistor is presented for CMOS image sensor and its analytical model is also established.With the technical parameter of the 0.6μm CMOS process,the bipolar junction photogate transistor is analyzed and simulated.The simulated results illustrate that the bipolar junction photogate transistor has the similar characteristics of the traditional photogate transistor.The photocurrent density of the bipolar junction photogate transistor increases exponentially with the incidence light power due to introducing the injection p+n junction.Its characteristic of blue response is rather improved compared to the traditional photogate transistor that benefits to increase the color photograph made up of the red,the green,and the blue.

Application of Laser Speckle Technology on the Detection of Agricultural Products

[Objective] The research aimed at investigating the application of laser speckle technology in agricultural products detection.[Method] This article described the basic principle of the laser speckle technology,provided a review of application development of the laser speckle technology in agricultural products detection,analyzed the problems in agriculture products detection using laser speckle technology and described the prospects of laser speckle technology in agricultural products detection.[Result] The laser speckle technology is a non-destructive detection technology for quality determination of agricultural products,which can be used to classify the agricultural products reasonably according to the quality of agricultural products.[Conclusion] The article provided reference and consult for laser speckle detection technology research.

Bubble Formation in Non-Newtonian Fluids Using Laser Image Measurement System

A self-developed laser image measurement system was established to study the behavior of bubble for- mation at a single orifice in non-Newtonian polyacrylamide(PAAm)solutions.Images of bubbles were captured by a CCD camera and volumes of bubbles were digitally analyzed online.The effects of rheological property of PAAm solution,orifice,reservoir,and gas flowrate on bubble formation were studied experimentally.It is found that the volume of bubble increases with the concentration of PAAm solution,the diameter of the orifice,and the gas flowrate,respectively,whereas little effect of reservoir is observed in experiments.

Fabrication of PdSe2/GaAs Heterojunction for Sensitive Near-Infrared Photovoltaic Detector and Image Sensor Application

In this study,we have developed a high-sensitivity,near-infrared photodetector based on PdSe2/GaAs heterojunction,which was made by transferring a multilayered PdSe2 film onto a planar GaAs.The as-fabricated PdSe2/GaAs heterojunction device exhibited obvious photovoltaic behavior to 808 nm illumination,indicating that the near-infrared photodetector can be used as a self-driven device without external power supply.Further device analysis showed that the hybrid heterojunction exhibited a high on/off ratio of 1.16×10^5 measured at 808 nm under zero bias voltage.The responsivity and specific detectivity of photodetector were estimated to be 171.34 mA/W and 2.36×10^11 Jones,respectively.Moreover,the device showed excellent stability and reliable repeatability.After 2 months,the photoelectric characteristics of the near-infrared photodetector hardly degrade in air,attributable to the good stability of the PdSe2.Finally,the PdSe2/GaAs-based heterojunction device can also function as a near-infrared light sensor.

A background refinement method based on local density for hyperspectral anomaly detection

For anomaly detection,anomalies existing in the background will affect the detection performance.Accordingly,a background refinement method based on the local density is proposed to remove the anomalies from thebackground.In this work,the local density is measured by its spectral neighbors through a certain radius which is obtained by calculating the mean median of the distance matrix.Further,a two-step segmentation strategy is designed.The first segmentation step divides the original background into two subsets,a large subset composed by background pixels and a small subset containing both background pixels and anomalies.The second segmentation step employing Otsu method with an aim to obtain a discrimination threshold is conducted on the small subset.Then the pixels whose local densities are lower than the threshold are removed.Finally,to validate the effectiveness of the proposed method,it combines Reed-Xiaoli detector and collaborative-representation-based detector to detect anomalies.Experiments are conducted on two real hyperspectral datasets.Results show that the proposed method achieves better detection performance.

Abundance quantification by independent component analysis of hyperspectral imagery for oil spill coverage calculation

The estimation of oil spill coverage is an important part of monitoring of oil spills at sea.The spatial resolution of images collected by airborne hyper-spectral remote sensing limits both the detection of oil spills and the accuracy of estimates of their size.We consider at-sea oil spills with zonal distribution in this paper and improve the traditional independent component analysis algorithm.For each independent component we added two constraint conditions:non-negativity and constant sum.We use priority weighting by higher-order statistics,and then the spectral angle match method to overcome the order nondeterminacy.By these steps,endmembers can be extracted and abundance quantified simultaneously.To examine the coverage of a real oil spill and correct our estimate,a simulation experiment and a real experiment were designed using the algorithm described above.The result indicated that,for the simulation data,the abundance estimation error is 2.52% and minimum root mean square error of the reconstructed image is 0.030 6.We estimated the oil spill rate and area based on eight hyper-spectral remote sensing images collected by an airborne survey of Shandong Changdao in 2011.The total oil spill area was 0.224 km^2,and the oil spill rate was 22.89%.The method we demonstrate in this paper can be used for the automatic monitoring of oil spill coverage rates.It also allows the accurate estimation of the oil spill area.

Single Camera 3-D Coordinate Measuring System Based on Optical Probe Imaging

A new vision coordinate measuring system--single camera 3 D coordinate measuring system based on optical probe imaging is presented. A new idea in vision coordinate measurement is proposed. A linear model is deduced which can distinguish six freedom degrees of optical probe to realize coordinate measurement of the object surface. The effects of some factors on the resolution of the system are analyzed. The simulating experiments have shown that the system model is available.

Optoelectronic Detecting System for Inner Walls of Pipes

This paper is concerned with a high characteristic image processing and recognition system that is used for inspecting real-time blemishes, streaks and cracks on the inner walls of high accuracy pipes. As a regular detector, the BP neural network is used for extracting features of the image inspected and classifying these images, it takes fully advantage of the function of artificial neural network, such as the information distributed memory, large scale self-adapting parallel processing, high fault-tolerant ability and so forth. Besides, an improved BP algorithm is used in the system for training the network, and making the learning procedure of the net converges to the minimum of overall situation at high rate.

Predictive Vegetation Mapping Approach Based on Spectral Data, DEM and Generalized Additive Models

This study aims to provide a predictive vegetation mapping approach based on the spectral data, DEM and Generalized Additive Models (GAMs). GAMs were used as a prediction tool to describe the relationship between vegetation and environmental variables, as well as spectral variables. Based on the fitted GAMs model, probability map of species occurrence was generated and then vegetation type of each grid was defined according to the probability of species occurrence. Deviance analysis was employed to test the goodness of curve fitting and drop contribution calculation was used to evaluate the contribution of each predictor in the fitted GAMs models. Area under curve (AUC) of Receiver Operating Characteristic (ROC) curve was employed to assess the results maps of probability. The results showed that: 1) AUC values of the fitted GAMs models are very high which proves that integrating spectral data and environmental variables based on the GAMs is a feasible way to map the vegetation. 2) Prediction accuracy varies with plant community, and community with dense cover is better predicted than sparse plant community. 3) Both spectral variables and environmental variables play an important role in mapping the vegetation. However, the contribution of the same predictor in the GAMs models for different plant communities is different. 4) Insufficient resolution of spectral data, environmental data and confounding effects of land use and other variables which are not closely related to the environmental conditions are the major causes of imprecision.

Fusion and Classification of Beijing-1 Small Satellite Remote Sensing Image for Land Cover Monitoring in Mining Area

In order to promote the application of Beijing-1 small satellite(BJ-1) remote sensing data,the multispectral and panchromatic images captured by BJ-1 were used for land cover classification in Pangzhuang Coal Mining.An improved Intensity-Hue-Saturation(IHS) fusion algorithm is proposed to fuse panchromatic and multispectral images,in which intensity component and panchromatic image are combined using the weights determined by edge pixels in the panchromatic image identified by grey absolute correlation degree.This improved IHS fusion algorithm outper-forms traditional IHS fusion method to a certain extent,evidenced by its ability in preserving spectral information and enhancing spatial details.Dempster-Shafer(D-S) evidence theory was adopted to combine the outputs of three member classifiers to generate the final classification map with higher accuracy than that by any individual classifier.Based on this study,we conclude that Beijing-1 small satellite remote sensing images are useful to monitor and analyze land cover change and ecological environment degradation in mining areas,and the proposed fusion algorithms at data and decision levels can integrate the advantages of multi-resolution images and multiple classifiers,improve the overall accuracy and produce a more reliable land cover map.

Kernel-based fisher discriminant analysis for hyperspectral target detection

A new method based on kernel Fisher discriminant analysis （KFDA） is proposed for target detection of hyperspectral images. The KFDA combines kernel mapping derived from support vector machine and the classical linear Fisher discriminant analysis （LFDA）, and it possesses good ability to process nonlinear data such as hyperspectral images. According to the Fisher rule that the ratio of the between-class and within-class scatters is maximized, the KFDA is used to obtain a set of optimal discriminant basis vectors in high dimensional feature space, All pixels in the hyperspectral images are projected onto the discriminant basis vectors and the target detection is performed according to the projection result. The numerical experiments are performed on hyperspectral data with 126 bands collected by Airborne Visible/Infrared Imaging Spectrometer （AVIRIS）, Tbe experimental results show the effectiveness of the proposed detection method and prove that this method has good ability to overcome small sample size and spectral variability in the hyperspectral target detection.

ManUfaCturing,Testing and Alignment of Sentinel-2MSl Telescope Mirrors

The ESA Sentinel-2 mission developed by European Aeronautic Defense and Space Compagny （EADS） Astrium will be devoted to Earth high resolution spectral imagery for the purpose of a global environmental monitoring. As a subcontractor of EADS Astrium, AMOS was responsible for the manufacturing of the instrument telescope mirrors and for the validation of the telescope alignment procedure. This paper details the mirror manufacturing sequences from mirror CVD-SiC cladding to surface figuring and coating, outlining the metrology steps and their corresponding accuracy budget. The telescope alignment process is described in connection with the tooling and techniques that helped achieve the required optical performance of less than 90 nm RMS wavefront error within the telescope field of view.Pierre Gloesenet

3-D Fiber Optic Fluorescent Detection System for Mineral Oilin Water

Parameter quantification principle of three-dimensional(3-D) fluorescent spe ctrum and its realization technique are studied. The portab le fiber-optic fluorescent measurer for mineral oil is given. Thr ee parameters of the exciting light wavelength, the wavelength and the intensity of the fluorescent light excited by the measured oil are expressed with 3-D co ordinates and are processed so as to be sampled again and to be curve fitted.

Real-time Data Communication in Photoelectric Image Detection System

High speed data communication between digital signal processor and the host is required to meet the demand of most real-time systems. PCI bus technology is a solution of this problem. The principle of data communication based on PCI has been explained. Meanwhile, the technology of data transfer between synchronous dynamic RAM(SDRAM) and an mapping space of on-chip memory(L2) by expansion direct memory access(EDMA) has also been realized.

Automatic segmentation of Colon Cancer Cells Based on Active Contour Method： A New Approach

Automatic interpretation of the images of colon cell biopsies requires automatic segmentation of these cells in the image obtained. The active contour method for image segmentation is a well known method for automatic detection of the cell contour. However, the application of this method on colon cell images was not effective. In this paper, the authors have proposed a new technique to reduce the analysis time needed to detect cells in a given image. This technique is based on the active contour method but now using a progressive division of the dimensions of the image to achieve convergence. The model proposed succeeded in detecting cells whose boundaries are not necessarily defined by a gradient. The initial curve can be anywhere in the image, and interior contours can be automatically detected. The developed algorithm was successfully applied on textured multispectral images of three types of cells, including benign hyperplasia （BH）, intraepithelial neoplasia （IN）, and carcinoma （Ca） cells.

Confocal Image 3D Surface Measurement with Optical Fiber Plate

A whole-field 3D surface measurement system for semiconductor wafer inspection is described.The system consists of an optical fiber plate,which can split the light beam into N^2 subbeams to realize the whole-field inspection.A special prism is used to separate the illumination light and signal light.This setup is characterized by high precision,high speed and simple structure.

MAXIMUM A POSTERIORI-BASED AUTOMATIC TARGET DETECTION IN SAR IMAGES

The paper presents an algorithm of automatic target detection in Synthetic Aperture Radar(SAR) images based on Maximum A Posteriori(MAP). The algorithm is divided into three steps. First, it employs Gaussian mixture distribution to approximate and estimate multi-modal histogram of SAR image. Then, based on the principle of MAP, when a priori probability is both unknown and learned respectively, the sample pixels are classified into different classes c = {target,shadow, background}. Last, it compares the results of two different target detections. Simulation results preferably indicate that the presented algorithm is fast and robust, with the learned a priori probability, an approach to target detection is reliable and promising.