黄土微结构图像处理的方法

本介绍了对黄土微结构电镜图像进行图像处理的常用方法。这些方法可以去除图像噪声，提高图像的对比度，使得图像便于进行人工解译或借助软件的图像分析。     

利用SPOT和ETM+影像进行县级土地利用调查--以河北省万全县为例

本文以SPOT和ETM 影像作为主要信息源，经过对图像进行几何纠正、配准、增强和融合等一系列处理后，在ARCVIEW GIS基础上，成功完成了对河北省万全县土地资源利用情况的调查分析。同时还对应用遥感技术成功获取土地资源利用信息的方法和技术进行了探讨。     

Sequence of faulting and deformation during the 2000 eruptions of the Usu Volcano, Hokkaido, Japan—interpretation and image analyses of aerial photographs

Significant faulting and deformation of the ground surface has been rarely known during volcanic eruptions. Usu Volcano, Hokkaido, Japan, is a unique example of deformation due to felsic magma intrusion. Usu Volcano has a history of such types of eruptions as phreatic, pumice eruption (Plinian type), pyroclastic flowing and lava doming since 1663. On March 31, 2000, phreatomagmatic to phreatic eruptions took place after 23 years of dormancy in the western piedmont, followed by explosions on the western flank of Usu Volcano. They were associated with significant deformation including faulting and uplift. The eruptions and deformation were continuing up to the end of May 2000.We identified the faulting using total nine sets of aerial photographs taken from before the eruption (March 31, 2000) to more than 1 year (April 27, 2001) after the end of the activity, and traced deformation processes through image processing using aerial photographs. We found that some of the new faults and the associated phreatic eruptions were related to old faults formed during the 1977–1981 eruptive episode.The image processing has revealed that the surface deformation is coincident with the area of faulting forming small grabens and the phreatic explosion vents. However, the faulting and main explosive eruptions did not take place in the highest uplift area, but along the margin. This suggests that the faulting and explosive activities were affected by small feeder channels diverging from the main magma body which caused the highest uplift.     

Image processing of 2D resistivity data for imaging faults

A methodology to locate automatically limits or boundaries between different geological bodies in 2D electrical tomography is proposed, using a crest line extraction process in gradient images. This method is applied on several synthetic models and on field data set acquired on three experimental sites during the European project PALEOSIS where trenches were dug. The results presented in this work are valid for electrical tomographies data collected with a Wenner-alpha array and computed with an l₁ norm (blocky inversion) as optimization method. For the synthetic cases, three geometric contexts are modelled: a vertical and a dipping fault juxtaposing two different geological formations and a step-like structure. A superficial layer can cover each geological structure. In these three situations, the method locates the synthetic faults and layer boundaries, and determines fault displacement but with several limitations. The estimated fault positions correlate exactly with the synthetic ones if a conductive (or no superficial) layer overlies the studied structure. When a resistive layer with a thickness of 6 m covers the model, faults are positioned with a maximum error of 1 m. Moreover, when a resistive and/or a thick top layer is present, the resolution significantly decreases for the fault displacement estimation (error up to 150%). The tests with the synthetic models for surveys using the Wenner-alpha array indicate that the proposed methodology is best suited to vertical and horizontal contacts. Application of the methodology to real data sets shows that a lateral resistivity contrast of 1:5–1:10 leads to exact faults location. A fault contact with a resistivity contrast of 1:0.75 and overlaid by a resistive layer with a thickness of 1 m gives an error location ranging from 1 to 3 m. Moreover, no result is obtained for a contact with very low contrasts (1:0.85) overlaid by a resistive soil. The method shows poor results when vertical gradients are greater than horizontal ones. This kind of image processing technique should be systematically used for improving the objectiveness of tomography interpretation when looking for limits between geological objects.     

Evaluation of a rule-based compositing technique for Landsat-5 TM and Landsat-7 ETM+ images

Image compositing is a multi-objective optimization process. Its goal is to produce a seamless cloud and artefact-free artificial image. This is achieved by aggregating image observations and by replacing poor and cloudy data with good observations from imagery acquired within the timeframe of interest. This compositing process aims to minimise the visual artefacts which could result from different radiometric properties, caused by atmospheric conditions, phenologic patterns and land cover changes. It has the following requirements: (1) image compositing must be cloud free, which requires the detection of clouds and shadows, and (2) the image composite must be seamless, minimizing artefacts and visible across inter image seams. This study proposes a new rule-based compositing technique (RBC) that combines the strengths of several existing methods. A quantitative and qualitative evaluation is made of the RBC technique by comparing it to the maximum NDVI (MaxNDVI), minimum red (MinRed) and maximum ratio (MaxRatio) compositing techniques. A total of 174 Landsat TM and ETM+ images, covering three study sites and three different timeframes for each site, are used in the evaluation. A new set of quantitative/qualitative evaluation techniques for compositing quality measurement was developed and showed that the RBC technique outperformed all other techniques, with MaxRatio, MaxNDVI, and MinRed techniques in order of performance from best to worst.     

Geometric-constrained multi-view image matching method based on semi-global optimization

Targeting at a reliable image matching of multiple remote sensing images for the generation of digital surface models, this paper presents a geometric-constrained multi-view image matching method, based on an energy minimization framework. By employing a geometrical constraint, the cost value of the energy function was calculated from multiple images, and the cost value was aggregated in an image space using a semi-global optimization approach. A homography transform parameter calculation method is proposed for fast calculation of projection pixel on each image when calculating cost values. It is based on the known interior orientation parameters, exterior orientation parameters, and a given elevation value. For an efficient and reliable processing of multiple remote sensing images, the proposed matching method was performed via a coarse-to-fine strategy through image pyramid. Three sets of airborne remote sensing images were used to evaluate the performance of the proposed method. Results reveal that the multi-view image matching can improve matching reliability. Moreover, the experimental results show that the proposed method performs better than traditional methods.     

多源地理空间矢量数据关联分析

针对多源地理空间矢量数据多来源、难以集成综合利用这一现状,本文提出了多源地理空间矢量数据关联方法,并以此为基础构建了多源地理空间矢量数据关联的可视与计算查询系统。首先,对多源地理空间矢量数据关联的概念及分类进行了定义。然后,以此为基础,提出了关联关系构建技术：自适应四叉树编码技术、扫描线技术、几何匹配及语义匹配技术。最后,为实现关联关系的直观展示,设计了原型系统。关联技术的提出可建立起多源地理空间矢量数据之间的关联关系,原型系统的构建也为用户综合利用多源地理空间矢量数据提供了平台,提高了数据的利用率及数据查询的效能。     

大比例尺全野外数字化测图

全野外数字化测图的基本思想是将野外采集的各种有关地物和地貌信息转化为数字形式,通过数据接口传输给计算机进行处理,得到内容丰富的电子地图,需要时由电子计算机的图形输出设备(如显示器、绘图仪)绘出地形图或各种专题地图。     

Astronomical Image Co-adding Method based on Wide-field Image Deconvolution

Due to the atmospheric turbulence, the static aberration, tracking and pointing errors of telescopes, the point spread functions (PSFs) in different fields of view are different. Meanwhile, there are different PSFs in the images obtained by different telescopes. The quality of co-adding image is limited by the image with the poorest quality, and finally the resolution and sensitivity of the quad-channel telescope will also be affected. Dividing the image into some regions with the same type of PSF, and deconvolving these regions can improve the quality of the co-adding image. According to this theory, an image restoration algorithm based on the PSF clustering is proposed. Firstly, this paper makes the PSF clustering analysis by using Self-Organizing Maps, and makes the image segmentation based on the result of the PSF clustering analysis, then using the clustered PSFs to make deconvolutions on the sub-images. Then, the restored sub-images after deconvolution are joined together. Finally, by through the image registration and co-adding, the image with a high signal to noise ratio can be obtained. The result shows that the signal to noise ratio of the astronomical images are improved with our method, and the detection capability on faint stars is also improved.