This PDF file contains the front matter associated with SPIE Proceedings Volume 8761, including the Title Page, Copyright information, Table of Contents, Introduction, and Conference Committee listing.

Laser speckle interferometry is used to detect micro-structure and its dynamic behavior of a sample surface by the statistical analysis of its laser speckle images. In this paper, the methodology of laser speckling and statistical analysis are studied with the aims to develop a non-contact, non-destructive surface sensing technique which potentially devices a compact, cost-effective tool for measuring the biological status of a plant by scanning its leaves. First, an auto-correlation based analysis method is proposed for the discrimination of various surface roughness levels using their laser speckle statistics. Second, techniques for dynamic speckle pattern analysis for the detection of the evolution of a time-varying sample surface are discussed. The effectiveness of proposed measurement methods are demonstrated via the experiment on a detached leaf.

In view of virtual plant has practical demands on quality, image and degree of realism animation in growing process of plant, this thesis design the animation based on mechanism and regularity of plant growth, and propose the design method based on 3D MAX technology. After repeated analysis and testing, it is concluded that there are modeling, rendering, animation fabrication and other key technologies in the animation design process. Based on this, designers can subdivid the animation into seed germination animation, plant growth prophase animation, catagen animation, later animation and blossom animation. This paper compounds the animation of these five stages by VP window to realize the completed 3D animation. Experimental result shows that the animation can realized rapid, visual and realistic simulatation the plant growth process.

To resist on general attacks, such as compression, noising and geometric distortion attacks is a common requirement for digital image watermarking or data hiding techniques comparing with rotation, scaling and translation (RST) attacks which are considered to be more challenging. Based on invariant centroid and LPM which is also used to analyze the angle of rotation and ratio of scaling influence after attacks of watermarked image combining with chaotic system and a novel adaptive coefficient α, this paper presents a robust and invisible digital image watermarking technology. The experiment results show that this method has high invisibility and robust, especially withstand RST attacks.

Compressive spectral imaging combines traditional spectral imaging method with new concept of compressive sensing thus has the advantages such as reducing acquisition data amount, realizing snapshot imaging for large field of view and increasing image signal-to-noise and its preliminary application effectiveness has been explored by early usage on the occasions such as high-speed imaging and fluorescent imaging. In this paper, the application potentiality for spatial coding compressive spectral imaging technique on rural survey is revealed. The physical model for spatial coding compressive spectral imaging is built on which its data flow procession is analyzed and its data reconstruction issue is concluded. The existing sparse reconstruction methods are reviewed thus specific module based on the two-step iterative shrinkage/thresholding algorithm is built so as to execute the imaging data reconstruction. The simulating imaging experiment based on AVIRIS visible band data of a specific selected rural scene is carried out. The spatial identification and spectral featuring extraction capacity for different ground species are evaluated by visual judgment of both single band image and spectral curve. The data fidelity evaluation parameters (RMSE and PSNR) are put forward so as to verify the data fidelity maintaining ability of this compressive imaging method quantitatively. The application potentiality of spatial coding compressive spectral imaging on rural survey, crop monitoring, vegetation inspection and further agricultural development demand is verified in this paper.

The dynamic visual image modeling for 3D synthetic scenes by using dynamic multichannel binocular visual image based on the mobile self-organizing network. Technologies of 3D modeling synthetic scenes have been widely used in kinds of industries. The main purpose of this paper is to use multiple networks of dynamic visual monitors and sensors to observe an unattended area, to use the advantages of mobile network in rural areas for improving existing mobile network information service further and providing personalized information services. The goal of displaying is to provide perfect representation of synthetic scenes. Using low-power dynamic visual monitors and temperature/humidity sensor or GPS installed in the node equipment, monitoring data will be sent at scheduled time. Then through the mobile self-organizing network, 3D model is rebuilt by synthesizing the returned images. On this basis, we formalize a novel algorithm for multichannel binocular visual 3D images based on fast 3D modeling. Taking advantage of these low prices mobile, mobile self-organizing networks can get a large number of video from where is not suitable for human observation or unable to reach, and accurately synthetic 3D scene. This application will play a great role in promoting its application in agriculture.

This paper proposes a Markov random field (MRF) model with adaptive selection multiresolution (MRF-AM) for texture image segmentation. By considering the wavelet decomposition and the morphological wavelet decomposition, MRFAM adaptively selects the multiresolution representation as features from the wavelet and morphological wavelet stepby- step. Then, the MRF is employed to model the features of adaptive multiresolution. The segmentation results are finally obtained by maximizing a posterior probability of the MRF. Experiments demonstrate that our method can improve the segmentation accuracy compared with the deterministic multi-resolution method.

To analyze the formation mechanism of the halo on low light level image intensifiers and the influencing factors on the halo size, a halo tester has been designed. Under the illumination between 10^-2 lx and 10^-4 lx, we use the tester to collect a 0.1922 mm hole image directly with CoolSNAP_K4 charge-coupled device (CCD) in a darkroom. The practical measurement result shows that the amplification ratio is 343.4. Then we put the super second and third generation image intensifiers after the hole, and the halo sizes of the hole images on the screens are determined as 0.2388 and 0.5533 mm respectively. The results are helpful to improve the quality of the low light level image intensifiers.

It is usually hard for traditional machine-learning-based classification algorithms such as Support Vector Machine (SVM) to classify similar characters in the process of license plate character recognition. In this paper, we introduced an efficient character recognition system based on a local, robust shape descriptor called the shape context to solve this problem. We also improved the matching strategy overcome shape context’s slow running speed. Experiment result shows the proposed algorithm has higher accuracy and quicker running speed compare to traditional machine- learning-based algorithms.

Study a new method for detecting fish freshness. During the experiment, we choose freshest fish-eyes images via digital camera to add computing the synthesis of the latest fish-eye image .Next figure out every image’s signal strength. Finally, we analysis relation between the change of the image’s energy and the value (pH, electrical conductivity, TVBN) by Modeling of Partial Least Squares Regression. The result shows that we can detect freshness of fish quickly, conveniently, simply and accurately through the fish-eye image energy change.

In this effort, we proposed an new image fusion technique, utilizing Renyi entropy’s object extraction and Non-Subsampled Contourlet Transform (NSCT), for improved visible effect of the image. NSCT is a multiscale transform method, it is a shift-invariant, linear phase, ‘‘true” two-dimensional transform that can decomposes an image into any directional sub-images to capture the intrinsic geometrical structure. In this paper we decompose visible image into 21, 22, and 23 directional sub-images at three different level respectively. Image enhancement is performed at the decomposition level and fused. Renyi entropy is a generalized information entropy. Infrared image can be divided into two parts of the object and the background through the maximum value of Renyi entropy. Image fusion is performed after NSCT and Renyi entropy. The fused image has significantly improved brightness and higher contrast than other images. In order to evaluate the proposed method, information entropy (IE), standard deviation (STD), spatial frequency (SF) and mutual information (MI) are adopted to compare with Laplace, wavelet, and NSCT et al. Results are shown that all evaluation value of the proposed method is higher than that of other methods, and it is a better image fusion method.

Based on remote sensing images, the panoramic views of land coverage distribution across a large geographic area can be accessed conveniently. In order to improve the accuracy of monitoring land use changes, the Chaos Genetic Algorithm was proposed. Chaos Immune Algorithm has capability of self-organizing, self-learning, self-recognition and self-memory, hence through the input samples the global optimization clustering center was found. And then the clustering center was employed to classify the view picture of remote sensing image. In this process, the ergodic property of chaos phenomenon was used to optimize the initial antibody population, so it could accelerate the convergence of Immune Algorithm. Through the clone selection operator, mutation operator and recruited antibody, local optimums were avoid. Chaos Immune Algorithm was applied to classify land use in Huainan –based on TM image. Based on confusion matrix, the classification of the Parallelepiped and Maximum likelihood methods were contrasted with Chaos Immune Algorithm. It is demonstrated that Chaos Immune Algorithm is superior to the two traditional algorithms, and its overall accuracy and Kappa coefficient reach 88.26% and 0.853respectively.

There are the geometric heterogeneity in different shapes of mouldboard ploughs. In order to evaluate the accuracy in measuring the 3D coordinates, and to study the simple mathematical surface which best fits the actual surface of the mouldboard plough, low-cost close-range photogrammetry were used for calculation of the 3D coordinates by co-linearity equation and direct linear transformation, which shoot the two image of 193 targets point marked on the model surface, and carry out binocular stereo matching according to the parallax factor. The results obtained indicate that the surface of a mouldboard plough can be shaped with an accuracy of approximately 1.3 mm, the 3D coordinates of 193 points on the surface of a plough are measured with great accuracy (root mean square 0.66 mm), with the adjustment of a cubic polynomial surface to just 25 control points randomly distributed over the surface of the plough. this surface can be applied to the theoretical analysis of the working process and the manufacture of the mouldboard plough.

This paper concerns the problem of standing tree volume measurement based on digital image processing. A computer and a camera were used in our work. Before the tree photo was taken, two red color marking labels were attached on the trunk. After the marking points and the tree trunk were extracted, the tree trunk edges were fitted with a high order curve. Then the volume of tree trunk of any height selected with a rectangle can be calculated. The experimental results show that the relative measurement error is low enough. So it is a viable method.

Ecology and water quality information monitoring has an important meaning to water and surrounding area. Compared with the traditional monitoring methods, getting water quality and ecological parameters, using remote sensing technology, can not only from the space and time scale extend the monitoring scope, but also greatly reduces the cost of monitoring. This paper mainly studies the design and development of multi-source image ecology and water quality information extraction system. This development method which using C#, Arc Engine and ENVI/IDL mixed model overcome the operation repeatability and calculating complexity, improve the efficiency of the system and provide information support for water environment evaluating and ecological monitoring.

Image segmentation is the first important step to image analysis and image processing. In this paper, according to color crops image characteristics, we firstly transform the color space of image from RGB to HIS, and then select proper initial clustering center and cluster number in application of mean-variance approach and rough set theory followed by clustering calculation in such a way as to automatically segment color component rapidly and extract target objects from background accurately, which provides a reliable basis for identification, analysis, follow-up calculation and process of crops images. Experimental results demonstrate that improved k-means clustering algorithm is able to reduce the computation amounts and enhance precision and accuracy of clustering.

Measuring wheat root length need manual measure by measuring rule, waste time and energy, low precision, aiming at this problem in this paper a connected component labeling algorithm for wheat root thinned image is presented. The algorithm realized on the basis of regional growth thought by dynamic queue list, only need one scan can finish label process. Aiming at label of wheat root thinned image, the algorithm compared with three algorithms, the experimental results show that the algorithm effect is good and suited to connecting component labeling for wheat root thinned image.

Antarctic krill (Euphausia superba Dana), one of the resources which have never been fished before, is full of development potential. The data of the ocean environment, generated from remote sensing, is the important parameter in analyzing the spatial and temporal distribution, the state of resource and the fishery work environment of Antarctic krill fishery. After downloading, extracting, clipping, registration, projection and calculation, we have got the information about the sea area and state data of Antarctic Krill fishery. Then we make the thematic map according to the data characteristic. From the distribution map of the 3 fishing areas in 2011, it is indicated that chlorophyll-a density is maximum in December and minimum in February. The sea surface temperature is maximum in February, and minimum in August. And the sea ice density is maximum in September and minimum in February. There are some differences in different season.

Intrinsic optical bistability (IOB) in Tm: YSGG (yttrium-scandium-gallium garnet) laser crystal pumped at 1um avalanche wavelength is predicted theoretically and studied numerically. The nonlinear rate equations of Tm: YSGG are given based on the nonlinear energy transfer processes. From the rate equations, the analytical formula of avalanche threshold condition is deduced in the steady-state approximation. Both the intrinsic bistability effect of population concentrations at Tm³⁺ levels versus pumping power and the influence of system parameters on IOB avalanche threshold are studied numerically. The results show that the avalanche threshold power of IOB can be changed by adjusting experimentally adjustable parameters such as the Tm³⁺ −dope concentration.

The absorption coefficients of chloroplast of leaf mustard were measured by a spectrophotometer. The leaves were collected from seven treatments with different lighting. The chlorophyll content was calculated following Arnon equation. LEDs for filling the light source can increase the conduction of plants. Compared with other treatments, Chlorophyll in the leaves got an higher concentration under the lamping of red LEDS to blue LEDS for 7:1 .

To effectively extract defective areas in fruits, the uneven intensity distribution that was produced by the lighting system or by part of the vision system in the image must be corrected. A methodology was used to convert non-uniform intensity distribution on spherical objects into a uniform intensity distribution. A basically plane image with the defective area having a lower gray level than this plane was obtained by using proposed algorithms. Then, the defective areas can be easily extracted by a global threshold value. The experimental results with a 94.0% classification rate based on 100 apple images showed that the proposed algorithm was simple and effective. This proposed method can be applied to other spherical fruits.

This current paper presented the kinetic analysis and model building using the Marquardt algorithm based on Gauss- Newton iteration for biomolecular interaction. This algorithm for biomolecular interaction analysis of the optical surface plasmon resonance was applied to implement the nonlinear fitting of association and disassociation process of the receptor to ligand (or the antibody to antigen). Finally, the kinetic parameters were obtained from the fitting curve established by the Marquardt algorithm. The results show that the Marquardt algorithm does not only reduce the dependence of initial value to avoid the divergence but also can greatly reduce the iterative regression times. The correlation coefficient R-squared of the original curve formed by OriginPro and the fitting curves constructed using the Marquardt algorithm in association process and in disassociation process were 0.99158 and 0.99693, respectively. Correspondingly, the kinetic parameters and affinity constants were evaluated using the obtained data from the fitting results.

In Fourier transform infrared spectrometer (FTIR), the optical path difference of laser metrology is applied to increase spectrum measure precision. However, due to the characteristics of laser single frequency and steady frequency, the uneven speed of moving mirror, circuit delay etc. cause the deviation of sampling point. In this paper, based on the interference theory of spectrometer, according to the Fourier contrary transform and methods of error analysis, the theory model between relative error of spectrum measure and the deviation of sampling point is established. Some simulation computations of the model have been done, the result indicates that, as a theory basis, the model can be applied in analyzing the sampling error of spectrometer and correction algorithm.

This paper indicates the feasibility to use near infrared (NIR) spectroscopy combined with synergy interval partial least squares (siPLS) algorithms as a rapid nondestructive method to estimate the soluble solid content (SSC) in strawberry. Spectral preprocessing methods were optimized selected by cross-validation in the model calibration. Partial least squares (PLS) algorithm was conducted on the calibration of regression model. The performance of the final model was back-evaluated according to root mean square error of calibration (RMSEC) and correlation coefficient (R² _c) in calibration set, and tested by mean square error of prediction (RMSEP) and correlation coefficient (R² _p) in prediction set. The optimal siPLS model was obtained with after first derivation spectra preprocessing. The measurement results of best model were achieved as follow: RMSEC = 0.2259, R² _c = 0.9590 in the calibration set; and RMSEP = 0.2892, R² _p = 0.9390 in the prediction set. This work demonstrated that NIR spectroscopy and siPLS with efficient spectral preprocessing is a useful tool for nondestructively evaluation SSC in strawberry.

Early detection of bruises on apples is important for an automatic apple sorting system. A hyperspectral imaging system with the wavelength range of 1000 to 2500nm was built for detecting bruises happened in an hour on ‘Fuji’ apples. Principal components analysis (PCA) was conducted on the hyperspecrtral images and the principal components images were compared. Three effective wavelengths 1060, 1329 and 1949nm were determined using the weighing coefficients plot of the best principal component (PC) image. A bruise detection algorithm based on PCA on the three effective wavelengths and a global threshold method was developed. Independent validation set of 50 intact and 50 bruised apples was used to evaluate the performance of the developed algorithm. Results show that 100% of the intact apples are correctly classified, 94% of the bruised apples are correctly recognized and the overall detection accuracy is 97%.

To reduce the number of the drivers in the conventional local dimming method for LCDs, a novel LED backlight local dimming system is proposed in this paper. The backlight of this system is generated by 2D discrete Hadamard transform and its matrix structured LED modules. Compared with the conventional 2D local dimming method, the proposed method costs much fewer drivers but with little degradation.

Silica optical fibres were used to measure colour (mg anthocyanin/g fresh berry weight) in samples of red wine grape homogenates via optical Fibre Evanescent Field Absorbance (FEFA). Colour measurements from 126 samples of grape homogenate were compared against the standard industry spectrophotometric reference method that involves chemical extraction and subsequent optical absorption measurements of clarified samples at 520 nm. FEFA absorbance on homogenates at 520 nm (FEFA_520h) was correlated with the industry reference method measurements of colour (R² = 0.46, n = 126). Using a simple regression equation colour could be predicted with a standard error of cross-validation (SECV) of 0.21 mg/g, with a range of 0.6 to 2.2 mg anthocyanin/g and a standard deviation of 0.33 mg/g. With a Ratio of Performance Deviation (RPD) of 1.6, the technique when utilizing only a single detection wavelength, is not robust enough to apply in a diagnostic sense, however the results do demonstrate the potential of the FEFA method as a fast and low-cost assay of colour in homogenized samples.

The ability of obtaining soil properties estimations from time and cost efficient remotely sensed techniques has been identified as a valuable technique as there is a great demand for larger amounts of good quality and inexpensive soil data to be used in environmental monitoring, modelling and precision agriculture. Visible (Vis) and Near Infrared (NIR) spectroscopy provides a good alternative that may be used to enhance or replace conventional methods of soil analysis. The aim of this paper is to evaluate the abilities of Vis (350-700 nm) and near infrared (700-2500 nm) for prediction of soil nutrients. In this instance we implemented Savitzky-Golay algorithm and Stepwise Multiple Linear Regression (SMLR) to construct calibration models. The soil nutrients examined were soil Total Nitrogen (N), Available Phosphorus (P) and Exchangeable Potassium (K). Our results revealed the accuracy of SMLR prediction in each of the Vis and NIR spectral regions. The NIR produced more accurate predictions for N and K; however, higher significant correlation was obtained using the Vis for available P. This work demonstrated Vis and NIR spectroscopy could be considered as a good tool to assess soil nutrients in Malaysian paddy fields.

A system of signal-to-noise ration (SNR)tester for LLL image intensifier is reconstructed . To realize SNR tester for UV image intensifier,the signal processing module and measurement software of the tester are reconstructed.The system of UV optical path is used. Based on photoemission mechanism of photocathode, noise factor of photocathode is concerned with quantum yield. In a range,noise factor of micro-channel plate(MCP) is decreased with the increase in gain. For a fixed size micro channel,the gain of MCP is increased as the voltage of MCP rises. The analyzed results show that when the voltage of MCP is in the range of -700V~-850V,the noise factor is monotonically decreased,when it exceed -850V, MCP is saturated. Although gain has continued to increase, noise factor is in the state of saturation. Experiment platform is builded according to SNR tester principle diagram of UV image intensifier.The results are given and analyzed. The conclusion is proved that the effect of voltage of MCP on the SNR of UV image intensifier is compatible with the analysis of theory.

Based on label stacking principles and coherent detection, we present a two-hop, coherent detected spectral amplitude code (SAC) labeled system to accomplish ultrafast packet forwarding for packet-switched metropolitan area networks. An optical switching network with two forwarding nodes, two 156 Mb/s SAC labels, and 40 Gb/s differential quadrature phase shift keying (DQPSK) payloads is demonstrated by computer simulation. The bit error rate (BER) performances of coherent detected SAC labels and high speed payload over 160 km fiber after two hops transmission are accessed, respectively.

The paper presents the concept of lever arm and boresight angle, the design requirements of calibration sites and the integrated calibration method of boresight angles of digital camera or laser scanner. Taking test data collected by Applanix’s LandMark system as an example, the camera calibration method is introduced to be piling three consecutive stereo images and OTF-Calibration method using ground control points. The laser calibration of boresight angle is proposed to use a manual and automatic method with ground control points. Integrated calibration between digital camera and laser scanner is introduced to improve the systemic precision of two sensors. By analyzing the measurement value between ground control points and its corresponding image points in sequence images, a conclusion is that position objects between camera and images are within about 15cm in relative errors and 20cm in absolute errors. By comparing the difference value between ground control points and its corresponding laser point clouds, the errors is less than 20cm. From achieved results of these experiments in analysis, mobile mapping system is efficient and reliable system for generating high-accuracy and high-density road spatial data more rapidly.

To improve the performance of GaAs NEA photocathodes, an exponential-doping structure GaAs material has been put forward, in which from the GaAs bulk-to-surface doping concentration is distributed exponentially from high to low. We apply this exponential-doping GaAs structure to the transmission-mode GaAs photocathodes. This sample was grown on the high quality p-type Be-doped GaAs (100) substrate by MBE. We have calculated the band-bending energy in exponential-doping GaAs emission-layer, and the total band-bending energy is 59 meV which helps to improve the photoexcited electrons movement towards surface for the thin epilayer. The integrated sensitivity of the exponential-doping GaAs photocathode samples reaches 1547uA/lm.

Compared with detecting tedium and complexity of current crop seeds, come up with a new single photon detection technique. Put seeds into camera bellows, process the single photon radiation. Then make an analysis and compare to crops spectrum by complicated circuitry and computer analysis software to acquire the quality of crops seeds. This analytical method enhances the work efficiency of disposable detect crops quality. It’s also provides a good mirror scheme to detect and analyze other organisms quality.

Handheld chlorophyll sensors is a very important technique to determine the timing and number of N applications, which can improve the fertilizer-N use efficiency and monitor leaf N status of irrigated rice. One solution-culture and two field experiments with four rice genotypes were conducted to obtain variables reflecting nitrogen (N) status at different developmental stages. The paper systemically compared SPAD indices calculated from the SPAD readings of various leaf positions and hyperspectral vegetation indices. The results showed that the indices RSI and RDSI were more reliable SPAD indices for estimating foliar N status in rice plant; In addition, from view of quickness and cheapness, chlorophyll meters are more suitable for estimating foliar N status in rice than reflectance spectroscopy on the basis of meeting accuracy requirements.

In this paper, a method which vectorizes and visualizes of 3-d terrain based on the contour line map using R2V and ArcGIS software is discussed. This method makes digitization and visualization easier, faster and more applicable. These data of contour line being vectorized and edited by R2V was imported into ArcGIS , finally the processed datum displayed in three-dimention manner. With the help of R2V and ArcGIS, digitizing of relief map and making DEM will be more effective and helpful for the technician in need.

The body length and weight are critical physiological parameters for fishes, especially eel-like fishes like swamp eel(Monopterusalbus).Fast and accurate measuring of body length is significant for swamp eel culturing as well as its resource investigation and protection. This paper presents an Android smart phone-based photogrammetry technology for measuring and estimating the length and weight of swamp eel. This method utilizes the feature that the ratio of lengths of two objects within an image is equal to that of in reality to measure the length of swamp eels. And then, it estimates the weight via a pre-built length-weight regression model. Analysis and experimental results have indicated that this method is a fast and accurate method for length and weight measurements of swamp eel. The cross-validation results shows that the RMSE (root-mean-square error) of total length measurement of swamp eel is0.4 cm, and the RMSE of weight estimation is 11 grams.

Take advantage of ample modern existing telecom network resources to rural areas may achieve it’s information society gradually. This includes the establishment of integrated rural information service platform, modern remote education center and electronic administration management platform for rural areas. The geographical and economic constraints must be overcome for structuring the rural service support system, in order to provide technical support, information products and information services to modern rural information service system. It is important that development an access platform based IP technology, which supports multi-service access in order to implement a variety of types of mobile terminal equipment adapter access and to reduce restrictions on mobile terminal equipment.

Considering the defect and imperfection of flame pixel point extraction and the bad environmental adaptability in the field of the present fire flame image segmentation algorithm, we put forward a kind of new algorithm based on the background difference method and fire flame color criterion. The adaptive background differencing method can detect and find objects which are moving or changing in the view field. The color criterion of fire flame can judge the color of flame of the moving objects, and then extract the flame image. Finally, the experimental results show that this algorithm has better adapt to the changing environment, and the flame extracting more accurately, perfect and stable.

To expand the current mobile phone short message service, and to make the contact between schools, teachers, parents and feedback of the modern school office system more timely and conveniently, designed and developed the Short Message System based on the Linux platform. The state-of-the-art principles and designed proposals in the Short Message System based on the Linux platform are introduced. Finally we propose an optimized secure access authentication method. At present, many schools,vbusinesses and research institutions ratify the promotion and application the messaging system gradually, which has shown benign market prospects.

Because of real wireless sensor network node distribution uniformity, this paper presents a clustering strategy based on the ant colony clustering algorithm (ACC-C). To reduce the energy consumption of the head near the base station and the whole network, The algorithm uses ant colony clustering on non-uniform clustering. The improve route optimal degree is presented to evaluate the performance of the chosen route. Simulation results show that, compared with other algorithms, like the LEACH algorithm and the improve particle cluster kind of clustering algorithm (PSC - C), the proposed approach is able to keep away from the node with less residual energy, which can improve the life of networks.

Three-dimensional shape of tidal creek widely distributed in the tidal flat of Jiangsu coast was simulated in this paper. Water lines of tidal creek were extracted from high spatial resolution remotely sensed data and used to derive the centerlines of tidal creek by the method of Thiessen polygon. From downstream to upstream, the profile shape of centerlines presents piecewise linear increase based on the intersect points of tidal branch in one tidal basin. So on basis of known elevation of intersect points, we calculated to gain 3D shape of centerline. And last, using step by step expansion simulated the whole 3D shape of tidal creek. The error analysis showed that the 95% error was between ± 0.3m. This study realized the 3D simulation of tidal creek. The result demonstrated that from point to line to body (2D- 3D) conversion was realized during this modeling process and 3D simulation method is effective. Due to complex natural condition and the lack of bathymetry data, terrain of tidal creek is difficult to obtain. So through this method we can only use a small number of measure points to easily obtain the 3D shape of tidal creek. It is very useful in topographic survey especially in Jiangsu coast where bathymetry is hard to carry out.

Cognition capability has been seen by researchers as the way forward for the design of next generation of Mobile Ad Hoc Networks (MANETs). The reason why a cognitive paradigm would be more suited to a MANET is because MANETs are highly dynamic networks. The topology may change very frequently during the operation of a MANET. Traffic patterns in MANETs can vary from time to time depending on the need of the users. The size of a MANET and node density is also very dynamic and may change without any predictable pattern. In a MANET environment, most of these parameters may change very rapidly and keeping track of them manually would be very difficult. Previous studies have shown that the performance of a certain routing approach in MANETs is dependent on the size of the network and node density. The choice of whether to use a reactive or proactive routing approach comes down to the network size parameter. Static or offline approaches to fine tune a MANET to achieve certain performance goals is hence not very productive as a lot of these parameters keep changing during the course of operation of MANETs. Similarly, the performance of MANETs would improve greatly if the MAC layer entity could operate in a more flexible manner. In this paper we propose a cognitive MANET design that will ensure that all these dynamic parameters are automatically monitored and decisions are based on the current status of these parameters.

The core components of Image intensifier is microchannel plate (MCP) and fluorescent screen component. The present paper deeply studies output signal-to-noise ratio (SNR) characteristics of MCP and fluorescent screen component. A tester system using to the evaluation of characteristics of the output SNR of MCP and fluorescent screen component, consists of a vacuum system, a surface electron source, mechanical mechanism components ,a high-voltage power supply system, a signal processing system, communication interfaces, a data acquisition and control system, computer system, and testing software. a hot cathode used as an electron source, generates a surface electron flow to provide the input signal. A photomultiplier tube is used to detection faceplate output brightness of the light spot. Then, the output SNR of MCP and fluorescent screen component is processed with a combination of methods of the hardware filter and digital filtering software. The output SNR of MCP and fluorescent screen component is measured under different conditions, and the results are analyzed. This test system Provide a technical to promote the image intensifier research, and experience to testing other parameters or in other areas of research.

In Scalable Video Coding (SVC) the coding efficiency for hierarchical prediction structures is highly dependent on how to choose the quantization parameters (QP) for pictures of different temporal layers. For pictures that have strong temporal correlation and pictures at low bitrate, large peak SNR (PSNR) fluctuations will be produced when using the strategy presented in the proposal JVT-P014. In order to decrease the fluctuations this paper proposed a new method which combines the persistence of vision to decrease the fluctuations of the video quality. Simulated results show that the proposed technique is efficient. When compared with the method in the proposal JVT-P014, the PSNR difference decreases is about 20%, and it is more effectively for the pictures with strong temporal correlation. The algorithm in this paper provides valuable references for further study of optimizing encoder.

Wireless Sensor Network (WSN) can be used in agriculture management. But hole can be produced in WSN due to the factors such as fault, energy depletion and so on, which can cause agricultural data incomplete. This fault can be repaired by deploying the mobile sensor nodes to patch the hole. The main optimization goal of this paper is to deploy the least mobile sensor nodes to make the cost of hole patching minimization. A hole patching strategy with the least mobile sensor nodes in WSN is proposed in this paper. Firstly, analyze geometric characteristics of the hole through detecting the hole. Next, deploy the mobile sensor nodes on the appropriate location to patch the hole according to the geometric characteristics. The strategy given in this paper includes two steps: (1) Choose the key intersection points from the set of intersection points of arc. (2) Determine the patching position of the mobile nodes to patch the hole. Finally, verify the effective of the strategy using a simulation experiment and analyze the performance based on the comparison of the experimental results. Using the hole patching strategy with the least mobile nodes in WSN can patch the hole completely and make the reparation cost minimization.

To solve network adaptive parameter determination problem of the pulse coupled neural network (PCNN), and improve the image segmentation results in image segmentation. The PCNN adaptive segmentation algorithm based on visual perception of information is proposed. Based on the image information of visual perception and Gabor mathematical model of Optic nerve cells receptive field, the algorithm determines adaptively the receptive field of each pixel of the image. And determines adaptively the network parameters W, M, and β of PCNN by the Gabor mathematical model, which can overcome the problem of traditional PCNN parameter determination in the field of image segmentation. Experimental results show that the proposed algorithm can improve the region connectivity and edge regularity of segmentation image. And also show the PCNN of visual perception information for segmentation image of advantage.