基于云教材建设思维的GIS专业“遥感数字图像处理”课程优化研究

遥感课程群是地理信息科学专业的主干内容,“遥感数字图像处理”更是其中最主要的专业核心课程之一。文章基于云教材建设思维对“遥感数字图像处理”课程展开优化,提出了相应改革方案,提高了前置与后置课程的衔接度、加强了课程与GIS专业契合度、进一步体现了地理科学学科特色。改革优化后的课程能切实提升学生的学习、实践以及探究能力,将为培养优秀GIS本科专业人才做出重要贡献。

Method for eliminating zero-order image in digital holography

For eliminating the zero-order image in digital holography, a new method using the differential of the hologram intensity instead of the hologram itself for numerical reconstruction is proposed. This method is based on digital image processing. By analyzing the spatial spectrum of the off-axis digital hologram, it theoretically proves that the zero-order image can be effectively eliminated by differential before reconstruction. Then, the detected hologram is processed in the program with differential and reconstruction. Both the theoretical analysis and digital reconstruction results show that it can effectively eliminate the large bright spot in the center of the reconstructed image caused by the zero-order image, improve the image quality significantly, and render a better contrast of the reconstructed image. This method is very simple and convenient due to no superfluous optical elements and requiring only one time record.

Measuring the Condition of Parking Lot by Image Processing

Aim To study the parking management in the condition of vehicles' increasing. Methods The methods of pattern recognition and image processing were used to analyze the eigenvalues of parking lot images. Results The automatic identification of every parking place in the parking plot was realized. The automatic measuring of parked vehicle count and parking lot utilization was completed. Conclusion It can complete the real time recognition, and has some practicabilities.

Numerical simulation of direct shear tests on mechanical properties of talus deposits based on self-adaptive PCNN digital image processing

The macro mechanical properties of materials with characteristics of large scale and complicated structural composition can be analyzed through its reconstructed meso-structures.In this work,the meso-structures of talus deposits that widely exist in the hydro-power engineering in the southwest of China were first reconstructed by small particles according to the in-situ photographs based on the self-adaptive PCNN digital image processing,and then numerical direct shear tests were carried out for studying the mechanical properties of talus deposits.Results indicate that the reconstructed meso-structures of talus deposits are more consistent with the actual situation because the self-adaptive PCNN digital image processing has a higher discrimination in the details of soil-rock segmentation.The existence and random distribution of rock blocks make the initial shear stiffness,the peak strength and the residual strength higher than those of the "pure soil" with particle size less than 1.25 cm apparently,but reduce the displacements required for the talus deposits reaching its peak shear strength.The increase of rock proportion causes a significant improvement in the internal friction angle of talus deposit,which to a certain degree leads to the characteristics of shear stress-displacement curves having a changing trend from the plastic strain softening deformation to the nonlinear strain hardening deformation,while an unconspicuous increase in cohesion.The uncertainty and heterogeneity of rock distributions cause the differences of rock proportion within shear zone,leading to a relatively strong fluctuation in peak strengths during the shear process,while movement features of rock blocks,such as translation,rotation and crossing,expand the scope of shear zone,increase the required shear force,and also directly lead to the misjudgment that the lower shear strength is obtained from the samples with high rock proportion.That,however,just explains the reason why the shear strength gained from a small amount of indoor test data is not consistent with engineering practice.

APPLICATION OF IMAGE PROCESSING TECHNIQUE IN SPM SYSTEM

Up to now the imported commercial scanning probe microscope(SPM) has not an automatic error correcting and reducing system.In this paper a software system is presented to solve this problem.This software system gives the average distance between the centers of mass of two adjacent atoms on the same horizontal line and its mean square root as well as the atoms shape and center of mass by filtering the measured image of a standard sample-highly oriented pyrolysis graphite(HOPG).This system forms the basis of SPMs automatic measurement error correcting.

Shape characterization of sand particles based on digital image processing technology

To characterize the shape of sand particles for concrete,a new method is proposed based on digital image processing(known as the DIP method).By analyzing sand particles projection,the length,width and thickness of sand were measured to characterize particle form.The area and perimeter were measured to characterize particle angularity.The results of the DIP method and Vernier caliper were compared to examine the accuracy of the DIP method.The sample size test was conducted to show the statistical significance of shape results measured by the DIP method.The practicality of the DIP method was verified by instance analysis.The results show that aspect ratios and roundness measured by the DIP method are equal to ones by the Vernier caliper.Results by DIP are dependent on the sand particle number,and at least 350 particles should be measured to represent the overall shape property of sand.The results show that the DIP method is able to distinguish the differences in the shape of sand particles.It achieves the direct measurement of sand particle thickness,and the characterization results of sand aspect ratios and roundness are accurate,statistically significant and practical.Therefore,the DIP method is suitable for sand particle shape characterization.

Identification of rice seed varieties using neural network

A digital image analysis algorithm based color and morphological features was developed to identify the six varieties （ey7954, syz3, xsl 1, xy5968, xy9308, z903） rice seeds which are widely planted in Zhejiang Province. Seven color and fourteen morphological features were used for discriminant analysis, Two hundred and forty kernels used as the training data set and sixty kernels as the test data set in the neural network used to identify rice seed varieties. When the model was tested on the test data set, the identification accuracies were 90.00%, 88.00%, 95.00%, 82.00%, 74.00%, 80.00% for ey7954, syz3, xsl1, xy5968, xy9308, z903 respectively.

Model heat source using actual distribution of laser power density for simulation of laser processing

The model of heat source(MHS) which reflects the thermal interaction between materials and laser during processing determines the accuracy of simulation results. To acquire desirable simulations results, although various modifications of heat sources in the aspect of absorption process of laser by materials have been purposed, the distribution of laser power density(DLPD) in MHS is still modeled theoretically. However, in the actual situations of laser processing, the DLPD is definitely different from the ideal models. So, it is indispensable to build MHS using actual DLPD to improve the accuracy of simulation results. Besides, an automatic modeling method will be benefit to simplify the tedious pre-processing of simulations. This paper presents a modeling method and corresponding algorithm to model heat source using measured DLPD. This algorithm automatically processes original data to get modeling parameters and provides a step MHS combining with absorption models. Simulations and experiments of heat transfer in steel plates irradiated by laser prove the mothed and the step MHS. Moreover, the investigations of laser induced thermal-crack propagation in glass highlight the signification of modeling heat source based on actual DLPD and demonstrate the enormous application of this method in the simulation of laser processing.

Improved Correlation for the Volume of Bubble Formed in Air-Water System

In order to address the bubble formation and movement in air-water two-phase flow,single bubble rising in stagnant water is experimentally studied by digital image processing.Bubbles are released individually from the submerged orifices with different diameters(1.81 mm,2.07 mm,2.98 mm,3.92 mm)at different detachment frequency.Images are recorded by a high-speed video camera and processed by digital image processing technique. The factors impacting the formed volume of bubble are discussed.The experimental results showed that a threshold of gas flow rate(400 mm 3 ·s- 1)divides the bubble formation into two regimes:the constant volume regime and the growing volume regime.Especially for the growing volume regime,the surface tension is taken into account.The bubble volume is consisted of two parts:the surface tension impacting part and the gas volume flow rate impacting part.An improved correlation for bubble volume prediction is developed for the two regimes and better coincidence with the experiment data than the previous models is obtained.

Experimental Study on Local Mass Transfer of Structured Packing with the Method of Flow Visualization

A chromochemical reactive mass transfer technique has been employed to study local mass transfer characteristics of structured packing. This technology adopted by experiment is an Ammonia Adsorption Method （AAM） that yields the surface distribution of transferred mass by analyzing the color distribution on a filter paper with the results of the color chemical reaction. A digital image processing technology is applied for data visualiza-tion. The three-dimensional plot of the local mass transfer coefficients shows that there exist three peak values on different positions of a unit cell of structured packing. In order to improve mass transfer efficiency of the structured packing, one piece of baffle is added between packing sheets. As a result, the average mass transfer coefficient increases by （10 20）% and the pressure drop decreases by （15-55）%.

Development of a mass model in estimating weight-wise particle size distribution using digital image processing

Particle size distribution of coarse aggregates through mechanical sieving gives results in terms of cumu- lative mass percent. But digital image processing generated size distribution of particles, while being fast and accurate, is often expressed in terms of area function or number of particles. In this paper, a mass model is developed which converts the image obtained size distribution to mass-wise distribution, mak- ing it readily comparable to mechanical sieving data. The concept of weight/particle ratio is introduced for mass reconstruction from 2D images of particle aggregates. Using this mass model, the effects of several particle shape parameters （such as major axis, minor axis, and equivalent diameter） on sieve-size of the particles is studied. It is shown that the sieve-size of a particle strongly depend upon the shape param- eters, 91% of its variation being explained by major axis, minor axis, bounding box length and equivalent diameter. Furthermore, minor axis gives an overall accurate estimate of particle sieve-size, error in mean size （D-50） being just 0.4%. However, sieve-size of smaller particles （〈20 ram） strongly depends upon the length of the smaller arm of the bounding box enclosing them and sieve-sizes of larger particles （〉20 mm） are highly correlated to their equivalent diameters. Multiple linear regression analysis has been used to generate overall mass-wise particle size distribution, considering the influences of all these shape parameters on particle sieve-size. Multiple linear regression generated overall mass-wise particle size distribution shows a strong correlation with sieve generated data. The adjusted R-square value of the regression analysis is found to be 99 percent （w.r,t cumulative frequency）. The method proposed in this paper provides a time-efficient way of producing accurate （up to 99%） mass-wise PSD using digital image processing and it can be used effectively to renlace the mechanical sieving.

New method to quantitatively evaluate the homogeneity of asphalt mixtures

To evaluate the homogeneity of asphalt mixtures,the images of sections obtained by cutting the asphalt mixtures specimen horizontally or vertically were analyzed with digital image processing techniques,and the particle area ratio was achieved by applying sector scan for horizontal specimen and vertical scan for vertical one.The research result indicates that the influence of random distribution of aggregates in cutting the specimen can be eliminated by using colored aggregates to distinguish coarse and fine aggregates and using color threshold to segment the images.Choosing three typical gradations,proving particle area ratio obeying normal distribution and using the variability of particle area ratio as an index,it is feasible to quantitatively evaluate the homogeneity of asphalt mixtures.

Autonomous optical navigation for interplanetary exploration based on information of earth-moon

The image elements of earth-center and moon-center are obtained by processing the images of earthand moon, these image elements in combination with the inertial attitude information and the moon ephemerisare utilized to obtain the probe initial position relative to earth, and the Levenberg-Marquardt algorithm is usedto determine the accurate probe position relative to earth, and the probe orbit relative to earth is estimated by u-sing the extended Kalman filter. The autonomous optical navigation algorithm is validated using the digital simu-lation.

MAXIMUM LIKELIHOOD ESTIMATION FOR INSAR IMAGE CO-REGISTRATION

This paper presents a closed-form robust phase correlation based algorithm for performing image registration to subpixel accuracy.The subpixel translational shift information is directly obtained from the phase of the normalized cross power spectrum by using Maximum Likelihood Estimation(MLE).The proposed algorithm also has slighter time complexity.Experimental results show that the proposed algorithm yields superior registration precision on the Cramér-Rao Bound(CRB) in the presence of aliasing and noise.

A New Edge-directed Subpixel Edge Localization Method

Localization of the inspected chip image is one of the key problems with machine vision aided surface mount devices (SMD) and other micro-electronic equipments. This paper presents a new edge-directed subpixel edge localization method. The image is divided into two regions, edge and non-edge, using edge detection to emphasize the edge feature. Since the edges of the chip image are straight, they have straight-line characteristics locally and globally. First, the line segments of the straight edge are located to subpixel precision, according to their local straight properties, in a 3×3 neighborhood of the edge region. Second, the subpixel midpoints of the line segments are computed. Finally, the straight edge is fitted using the midpoints and the least square method, according to its global straight property in the entire edge region. In this way, the edge is located to subpixel precision. While fitting the edge, the irregular points are eliminated by the angles of the line segments to improve the precision. We can also distinguish different edges and their intersections using the angles of the line segments and distances between the edge points, then give the vectorial result of the image edge with high precision.

Automatic recognition and quantitative analysis of Ω phases in Al-Cu-Mg-Ag alloy

The main methods of the second phase quantitative analysis in current material science researches are manual recognition and extracting by using software such as Image Tool and Nano Measurer. The weaknesses such as high labor intensity and low accuracy statistic results exist in these methods. In order to overcome the shortcomings of the current methods, the Ω phase in A1-Cu-Mg-Ag alloy is taken as the research object and an algorithm based on the digital image processing and pattern recognition is proposed and implemented to do the A1 alloy TEM （transmission electron microscope） digital images process and recognize and extract the information of the second phase in the result image automatically. The top-hat transformation of the mathematical morphology, as well as several imaging processing technologies has been used in the proposed algorithm. Thereinto, top-hat transformation is used for elimination of asymmetric illumination and doing Multi-layer filtering to segment Ω phase in the TEM image. The testing results are satisfied, which indicate that the Ω phase with unclear boundary or small size can be recognized by using this method. The omission of these two kinds of Ω phase can be avoided or significantly reduced. More Ω phases would be recognized （growing rate minimum to 2% and maximum to 400% in samples）, accuracy of recognition and statistics results would be greatly improved by using this method. And the manual error can be eliminated. The procedure recognizing and making quantitative analysis of information in this method is automatically completed by the software. It can process one image, including recognition and quantitative analysis in 30 min, but the manual method such as using Image Tool or Nano Measurer need 2 h or more. The labor intensity is effectively reduced and the working efficiency is greatly improved.

COMPREHENSIVE INTEGRATION METHODS AND APPLICATION OF GRAVITY-MAGNETIC DATA IMAGE

the technique of image processing and analysis of gravity and magnetic data is one of themost effective ways to extract geological information from gravity and msanetic data. The presentpaper investigates, from an angle of generalized joint inversion, thc methods and procedures ofcomprehensive processing of multi-source geological image , and a specific example in Huai Nan coalfield is given here as well.

Infrared Real-time Thermal System Based on DSP

An infrared real-time imaging system using DSP(digital signal processor) as the kernel of digital signal processing board is presented. In this system, the imaging difference and nonuniformity correction method is developed on the chip taking advantage of DSP with high speed. The method combines hardware and software together, so that the difficulty for realizing such a method with other hardware can be overcome.

A New Method of Color Edge Detection Based on Local Structure Analysis

Human's real life is within a colorful world. Compared to the gray images, color images contain more information and have better visual effects. In today's digital image processing, image segmentation is an important section for computers to "understand" images and edge detection is always one of the most important methods in the field of image segmentation. Edges in color images are considered as local discontinuities both in color and spatial domains. Despite the intensive study based on integration of single-channel edge detection results, and on vector space analysis, edge detection in color images remains as a challenging issue.

Applying Digital Image Processing to Evaluate a Extraction Method of Cartographic Features in Digital Images

A topic studied in cartography is to make the extraction of cartographic features that provide the update of cartographic maps more easily. For this reason many automatic routines were created with the intent to perform the features extraction. Despite of all studies about this, some features cannot be found by the algorithm or it can extract some pixels unduly. So the current article aims to show the results with the software development that uses the original and reference image to calculate some statistics about the extraction process. Furthermore, the calculated statistics can be used to evaluate the extraction process.