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.     

The dynamic characteristics and migration of a pyramid dune

The results of wind tunnel experiments and field observations show that when the intersection angle between airflow direction and dune crest (ridge) line is > 30°, a reverse vortex is formed. Because of the convergence of sand streams from the windward and lee slopes at the crest, sand accumulates in the crestal region, causing vertical growth. Nevertheless, studies also show that the common asymmetry of the two slopes of a dune may significantly influence the evolution of arms of a pyramid dune. The migration rates of pyramid dunes are mediated by the interplay of their arms moving transversely and the vertical growth in response to the variations in wind regimes. Comparing the effects of airflow transverse to a given arm with longitudinal airflow, it is indicated that the transverse airflow is more significant in controlling the arms of pyramid dunes. The whole body of the studied pyramid dune, particularly the upper quarter section, migrated SE direction during the monitoring period. The patterns of wind erosion and deposition change alternately with seasonal variations in wind directions. The W, NE and SE sides undergo constant erosion, deposition and both erosion and deposition, respectively. The results of long-term monitoring of a pyramid dune show that southerly winds, resulting from a local circulation, markedly affect the transverse migration of the whole pyramid dune.     

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.     

Semantic segmentation of high spatial resolution images with deep neural networks

Availability of reliable delineation of urban lands is fundamental to applications such as infrastructure management and urban planning. An accurate semantic segmentation approach can assign each pixel of remotely sensed imagery a reliable ground object class. In this paper, we propose an end-to-end deep learning architecture to perform the pixel-level understanding of high spatial resolution remote sensing images. Both local and global contextual information are considered. The local contexts are learned by the deep residual net, and the multi-scale global contexts are extracted by a pyramid pooling module. These contextual features are concatenated to predict labels for each pixel. In addition, multiple additional losses are proposed to enhance our deep learning network to optimize multi-level features from different resolution images simultaneously. Two public datasets, including Vaihingen and Potsdam datasets, are used to assess the performance of the proposed deep neural network. Comparison with the results from the published state-of-the-art algorithms demonstrates the effectiveness of our approach.     

一种基于复合金字塔模型的三维模型数据组织方法

针对异构三维模型数据的统一组织和集成管理问题,本文以目前主流金字塔模型、三维场景瓦片的数据组织方法和地图服务规范等相关技术为基础,提出了一种基于复合金字塔模型的三维模型数据组织方法。该方法首先构建覆盖测区的地理格网模型,以此作为异构三维模型数据集成的空间框架。其次,建立三维模型数据与地理格网单元的映射关系,从而构建复合金字塔模型,实现异构三维模型数据的统一管理。最后,在数据结构上对现有数据格式进行扩展,设计了一种面向网络传输的数据格式储存三维模型数据,完成异构三维模型数据的一体化存储。试验结果表明,该方法能够实现异构三维模型数据统一组织与集成管理。     

一种快速的天文图像模拟方法及分析

图像模拟在天文学研究中已经发挥越来越重要的作用,其重要性主要表现在以下几方面:通过模拟可以为准备研制的天文观测设备评估提供重要的依据;通过对模拟数据的处理可以验证数据处理的算法。对图像模拟的整个过程进行描述,并在计算上对图像模拟的局部方法进行优化,使模拟结果能够高效准确的生成。主要工作包含以下几方面:对天体形态的模拟,包括点源(如恒星)和展源(星系),这里主要对展源建模;模拟观测条件,主要是仪器和天光背景等产生的噪声;模拟点扩散函数;从计算和程序的方法对计算流程进行优化;对结果进行分析。采用的数据是哈勃超深空场(HUDF) ACS WFC i(F775)波段的数据,其极限星等达到29等。通过对模拟结果的分析,可以看出该方法能够快速并且较为准确地对星系图像进行模拟。     

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.     

控制点影像库在遥感影像几何纠正中的应用

影像几何纠正是遥感图像处理的重要技术。为了克服现有方法在实际应用中的不足,提出利用控制点影像库进行影像自动匹配,然后进行几何变化的方式。这种方法简单有效,快速稳定,匹配得到的同名点数量足够且分布均匀,并通过引入最小二乘匹配使配准达到子像素精度,提高几何纠正的速度与可靠性。