An ASIFT-based local registration method for satellite imagery

Imagery registration is a fundamental step, which greatly affects later processes in image mosaic, multi-spectral image fusion, digital surface modelling, etc., where the final solution needs blending of pixel information from more than one images. It is highly desired to find a way to identify registration regions among input stereo image pairs with high accuracy, particularly in remote sensing applications in which ground control points (GCPs) are not always available, such as in selecting a landing zone on an outer space planet. In this paper, a framework for localization in image registration is developed. It strengthened the local registration accuracy from two aspects: less reprojection error and better feature point distribution. Affine scale-invariant feature transform (ASIFT) was used for acquiring feature points and correspondences on the input images. Then, a homography matrix was estimated as the transformation model by an improved random sample consensus (IM-RANSAC) algorithm. In order to identify a registration region with a better spatial distribution of feature points, the Euclidean distance between the feature points is applied (named the S criterion). Finally, the parameters of the homography matrix were optimized by the Levenberg–Marquardt (LM) algorithm with selective feature points from the chosen registration region. In the experiment section, the Chang’E-2 satellite remote sensing imagery was used for evaluating the performance of the proposed method. The experiment result demonstrates that the proposed method can automatically locate a specific region with high registration accuracy between input images by achieving lower root mean square error (RMSE) and better distribution of feature points

Evaluation of positioning error-induced pixel shifts on satellite linear push-broom imagery

Georeferencing is one of the major tasks of satellite-borne remote sensing. Compared to traditional indirect methods, direct georeferencing through a Global Positioning System/inertial navigation system requires fewer and simpler steps to obtain exterior orientation parameters of remotely sensed images. However, the pixel shift caused by geographic positioning error, which is generally derived from boresight angle as well as terrain topography variation, can have a great impact on the precision of georeferencing. The distribution of pixel shifts introduced by the positioning error on a satellite linear push-broom image is quantitatively analyzed. We use the variation of the object space coordinate to simulate different kinds of positioning errors and terrain topography. Then a total differential method was applied to establish a rigorous sensor model in order to mathematically obtain the relationship between pixel shift and positioning error. Finally, two simulation experiments are conducted using the imaging parameters of Chang’ E-1 satellite to evaluate two different kinds of positioning errors. The experimental results have shown that with the experimental parameters, the maximum pixel shift could reach 1.74 pixels. The proposed approach can be extended to a generic application for imaging error modeling in remote sensing with terrain variation

Subsidence monitoring of offshore platforms

AbstractThe normal subsidence monitoring technologies, used in civil engineering, are hard to apply in ocean engineering. Because it is hard to find a fixed reference for subsidence monitoring. A new method, which is suitable for subsidence monitoring of offshore platforms, is proposed in this paper. Firstly, the compression characteristic of the soil was analyzed and the harms of subsidence are discussed. Based on the analysis, the subsidence monitoring method was given. Finally, an real application is shown. Some advanced measurement technologies, such as the FBG strain measurement techniques and so on, were used in this application. The real application indicates that the new method is suitable for the subsidence monitoring of offshore platforms

Panoramic mosaics from Chang’E-3 PCAM images at Point A

This paper presents a unique approach for panoramic mosaics based on Moon surface images from the Chang’E-3 (CE-3) mission, with consideration of the exposure time and external illumination changes in CE-3 Panoramic Camera (PCAM) imaging. The engineering implementation involves algorithms of image feature points extraction by using Speed-Up Robust Features (SURF), and a newly defined measure is used to obtain the corresponding points in feature matching. Then, the transformation matrix is calculated and optimized between adjacent images by the Levenberg–Marquardt algorithm. Finally, an image is reconstructed by using a fade-in-fade-out method based on linear interpolation to achieve a seamless mosaic. The developed algorithm has been tested with CE-3 PCAM images at Point A (one of the rover sites where the rover is separated from the lander). This approach has produced accurate mosaics from CE-3 PCAM images, as is indicated by the value of the Peak Signal to Noise Ratio (PSNR), which is greater than 31 dB between the overlapped region of the images before and after fusion

miRAS: a data processing system for miRNA expression profiling study

<p>Abstract</p> <p>Background</p> <p>The study of microRNAs (miRNAs) is attracting great considerations. Recent studies revealed that miRNAs play as important regulators of gene expression and some even as cancer players or inhibitors. Many studies try to discover new miRNAs and reveal the miRNA expression profile in cancer using a SAGE-based total RNA clone method. However, the data processing of this method is labor-intensive with several different biological databases and more than ten data processing steps involved.</p> <p>Results</p> <p>With miRAS, miRNAs and possible miRNA candidates contained in the submitted sequencing data were obtained together with their expression profile. The functions of known and predicted miRNAs were then analyzed by miRNA target prediction followed by target gene annotations. Finally, to extract the biological significance of the miRNAs in the samples, further annotations of the known miRNA and target genes were performed by collecting the public expression datasets of miRNA and target genes in normal and cancer tissues.</p> <p>Conclusion</p> <p>We introduce a web-based analysis platform called miRNA Analysis System (miRAS), for processing and analyzing of the sequence data obtained from the total RNA clone method. The system was built on generalizing the study of a liver cancer cell line total RNA sequencing project. miRAS is freely available on the web.</p

Correlation between intercalated magnetic layers and superconductivity in pressurized EuFe2(As0.81P0.19)2

We report comprehensive high pressure studies on correlation between intercalated magnetic layers and superconductivity in EuFe2(As0.81P0.19)2 single crystal through in-situ high pressure resistance, specific heat, X-ray diffraction and X-ray absorption measurements. We find that an unconfirmed magnetic order of the intercalated layers coexists with superconductivity in a narrow pressure range 0-0.5GPa, and then it converts to a ferromagnetic (FM) order at pressure above 0.5 GPa, where its superconductivity is absent. The obtained temperature-pressure phase diagram clearly demonstrates that the unconfirmed magnetic order can emerge from the superconducting state. In stark contrast, the superconductivity cannot develop from the FM state that is evolved from the unconfirmed magnetic state. High pressure X-ray absorption (XAS) measurements reveal that the pressure-induced enhancement of Eu's mean valence plays an important role in suppressing the superconductivity and tuning the transition from the unconfirmed magnetic state to a FM state. The unusual interplay among valence state of Eu ions, magnetism and superconductivity under pressure may shed new light on understanding the role of the intercalated magnetic layers in Fe-based superconductors

Analysis of traveling wave based fault location method for distribution network with image processing

Laws of traveling wave data related to fault location for medium voltage distribution network are discussed and summarized. Given the tree structure of a distribution network, an image of nodes voltage is created combining the use of real-time traveling wave meters at all nodes of the tree. The novelty of this paper is that travelling wavefront are analyzed based on the dynamic changes of these images. Based on principle of the traditional fault location with traveling wave-based method for transmission networks, traveling wave data of fault location for medium voltage distribution networks are plotted in order to estimate propagation velocity and distance between the fault position and the reference node. The results indicate that taking advantage of the laws of data related to first wave front can improve the reliability of the fault location for medium voltage networks