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  • Articles  (480)
  • 2015-2019  (480)
  • 2016  (480)
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  • 2015-2019  (480)
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  • 1
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    Dielectric Response of Corn Leaves to Water Stress (2016)
    Institute of Electrical and Electronics Engineers (IEEE)
    Details
    Publication Date: 2016-12-31
    Description: Radar backscatter from a vegetated surface is sensitive to direct backscatter from the canopy and two-way attenuation of the signal as it travels through the canopy. Both mechanisms are affected by the dielectric properties of the individual elements of the canopy, which are primarily a function of water content. Leaf water content of corn can change considerably during the day and in response to water stress, and model simulations suggested that this significantly affects radar backscatter. Understanding the influence of water stress on leaf dielectric properties will give insight into how the plant water status changes in response to water stress and how radar can be used to detect vegetation water stress. We used a microstrip line resonator to monitor the changes in its resonant frequency at corn leaves, due to variations in dielectric properties. This letter presents the in vivo resonant frequency measurements during field experiments with and without water stress, to understand the dielectric response due to stress. The resonant frequency of the leaf around the main leaf of the stressed plant showed increasing diurnal differences. The dielectric response of the unstressed plant remained stable. This letter shows the clear statistically significant effect of water stress on variations in resonant frequency at individual leaves.
    Print ISSN: 1545-598X
    Electronic ISSN: 1558-0571
    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
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  • 2
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    Multiple-Reflection Noise Attenuation Using Adaptive Randomized-Order Empirical Mode Decomposition (2016)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2016-12-31
    Description: We propose a novel approach for removing noise from multiple reflections based on an adaptive randomized-order empirical mode decomposition (EMD) framework. We first flatten the primary reflections in common midpoint gather using the automatically picked normal moveout velocities that correspond to the primary reflections and then randomly permutate all the traces. Next, we remove the spatially distributed random spikes that correspond to the multiple reflections using the EMD-based smoothing approach that is implemented in the $f-x$ domain. The trace randomization approach can make the spatially coherent multiple reflections random along the space direction and can decrease the coherency of near-offset multiple reflections. The EMD-based smoothing method is superior to median filter and prediction error filter in that it can help preserve the flattened signals better, without the need of exact flattening, and can preserve the amplitude variation much better. In addition, EMD is a fully adaptive algorithm and the parameterization for EMD-based smoothing can be very convenient.
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    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
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  • 3
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    RFI Mitigation in Aperture Synthesis Radiometers Using a Modified CLEAN Algorithm (2016)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2016-12-31
    Description: For aperture synthesis radiometers, sparse samplings on the $u$ - $v$ frequency plane cause undesirable sidelobes in the synthesized beam. Through these sidelobes, artificial sources emitting in the protected 1400–1427 MHz band contaminate the retrievals of the soil moisture and ocean salinity (SMOS) from MIRAS measurements. One effective way to correct the artificial interferences is to create a synthetic signal to compensate for the interference’s impact. Based on the similar idea, in this letter, we describe an algorithm to compensate for the interference’s impact by constructing an artificial signal as close as possible to the Gaussian beam. Numerical studies using synthetic and real SMOS data have been carried out to demonstrate that the proposed algorithm outperforms the classical CLEAN algorithm in correcting the impact of the extended radio frequency interference source.
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    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
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  • 4
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    Region-of-Interest Coding Based on Saliency Detection and Directional Wavelet for Remote Sensing Images (2016)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2016-12-31
    Description: With growing contradiction between the high-speed acquisition of remote sensing data and the low-speed data storage and transmission, the advantages of giving higher priority to a region of interest (ROI) in compression have become prominent. Previous research focused on ROI coding, rather than automatic ROI extraction. However, accurate ROI extraction can significantly improve coding efficiency. In this letter, we propose an automatic ROI extraction based on the improved normal directional lifting wavelet transform (LWT). Then, the compression efficiency is enhanced by a novel tangent directional LWT to reduce the signal energy of high-frequency subbands. Finally, the autogenerated ROIs are encoded by a new multibitplane alternating shift method, which supports not only arbitrarily shaped ROI coding, but also flexible adjustment of compression quality in the ROI and the background. The experimental results demonstrate that our method can effectively highlight the ROIs with well-defined boundaries, meanwhile improving the ROI coding with better visual quality.
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    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
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  • 5
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    Semiautomatic Registration of Terrestrial Laser Scanning Data Using Perspective Intensity Images (2016)
    Institute of Electrical and Electronics Engineers (IEEE)
    Details
    Publication Date: 2016-12-31
    Description: Point cloud registration is an important procedure for terrestrial laser scanning data processing. Artificial targets are usually used in practice to guarantee a robust registration. However, installing and locating targets are labor-intensive for large surveying and mapping project. A methodology for semiautomatic registration of terrestrial point clouds using perspective intensity images is presented in this letter. To register two point clouds, perspective intensity image series of the scanning area are first generated from the point clouds. Then, corner points are extracted from the generated perspective intensity images and are interactively selected as tie points. The 3-D coordinates of the selected tie points are directly obtained or estimated using least squares method. Registration parameters are solved using singular value decomposition. To improve robustness and accuracy of the registration, random sample consensus is used to remove outliers in the tie points. The robustness and effectiveness of the presented methodology is demonstrated by experimental results.
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    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
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  • 6
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    Exponential Discriminative Locality Alignment for Hyperspectral Image Classification (2016)
    Institute of Electrical and Electronics Engineers (IEEE)
    Details
    Publication Date: 2016-12-31
    Description: Metric learning algorithms have been widely applied for hyperspectral image (HSI) dimensionality reduction and classification. One of the metric learning algorithms proposed recently is discriminative locality alignment (DLA). The DLA attacks the distribution nonlinearity of samples, and preserves the discriminative ability. However, the DLA needs to manually adjust a parameter called scaling factor and produce mutually correlated discriminant vectors that may lead to unsatisfactory classification results. In this letter, a modified DLA algorithm, i.e., quotient DLA (QDLA), is proposed to solve the problems outlined previously. Moreover, we extend QDLA to a novel exponential DLA (EDLA) algorithm, which can achieve a more effective transformation from a nonlinear mapping of original data into a new space. The classification results with HSIs demonstrate that the performances of the proposed EDLA are better than other related methods.
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    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
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  • 7
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    Drone Classification Using Convolutional Neural Networks With Merged Doppler Images (2016)
    Institute of Electrical and Electronics Engineers (IEEE)
    Details
    Publication Date: 2016-12-31
    Description: We propose a drone classification method based on convolutional neural network (CNN) and micro-Doppler signature (MDS). The MDS only presents Doppler information in time domain. The frequency domain representation of MDS is called as cadence-velocity diagram (CVD). To analyze the Doppler information of drone in time and frequency domain, we propose a new image by merging MDS and CVD, as merged Doppler image. GoogLeNet, a CNN structure, is utilized for the proposed image data set because of its high performance and optimized computing resources. The image data set is generated by the returned Ku-band frequency modulation continuous wave radar signal. Proposed approach is tested and verified in two different environments, anechoic chamber and outdoor. First, we tested our approach with different numbers of operating motor and aspect angle of a drone. The proposed method improved the accuracy from 89.3% to 94.7%. Second, two types of drone at the 50 and 100 m height are classified and showed 100% accuracy due to distinct difference in the result images.
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    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
    Published by Institute of Electrical and Electronics Engineers (IEEE)
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  • 8
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    Distortion Magnetic Field Compensation of Geomagnetic Vector Measurement System Using a 3-D Helmholtz Coil (2016)
    Institute of Electrical and Electronics Engineers (IEEE)
    Details
    Publication Date: 2016-12-31
    Description: The magnetic interferential fields, such as soft-iron and hard-iron interferences, will seriously affect the accuracy of geomagnetic vector measurement system, and thus should be compensated. In this letter, a new compensation method using a 3-D Helmholtz coil is proposed. As a first step, the geomagnetic vector measurement system is exposed to different directions and the magnitudes of magnetic field generated by a 3-D Helmholtz coil to construct the equations of error model, and soft-iron parameters can be estimated by solving linear equations. Then, hard-iron parameters are estimated by changing the fixation direction of the three-axis magnetometer. Finally, all the estimated parameters are used for compensating distortion magnetic fields. In order to verify the effectiveness of the proposed method, the experiment is conducted, and the results demonstrate that the proposed method contributes to the accuracy improvement of geomagnetic vector measurement system.
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    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
    Published by Institute of Electrical and Electronics Engineers (IEEE)
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  • 9
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    A New Sparse Subspace Clustering Algorithm for Hyperspectral Remote Sensing Imagery (2016)
    Institute of Electrical and Electronics Engineers (IEEE)
    Details
    Publication Date: 2016-12-31
    Description: Robust techniques such as sparse subspace clustering (SSC) have been recently developed for hyperspectral images (HSIs) based on the assumption that pixels belonging to the same land-cover class approximately lie in the same subspace. In order to account for the spatial information contained in HSIs, SSC models incorporating spatial information have become very popular. However, such models are often based on a local averaging constraint, which does not allow for a detailed exploration of the spatial information, thus limiting their discriminative capability and preventing the spatial homogeneity of the clustering results. To address these relevant issues, in this letter, we develop a new and effective $ell _{2} $ -norm regularized SSC algorithm which adds a four-neighborhood $ell _{2} $ -norm regularizer into the classical SSC model, thus taking full advantage of the spatial-spectral information contained in HSIs. The experimental results confirm the potential of including the spatial information (through the newly added $ell _{2} $ -norm regularization term) in the SSC framework, which leads to a significant improvement in the clustering accuracy of SSC when applied to HSIs.
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    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
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  • 10
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    Rough-Set-Based Color Channel Selection (2016)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2016-12-31
    Description: Color channel selection is essential for accurate segmentation of sky and clouds in images obtained from ground-based sky cameras. Most prior works in cloud segmentation use threshold-based methods on color channels selected in an ad hoc manner. In this letter, we propose the use of rough sets for color channel selection in visible-light images. Our proposed approach assesses color channels with respect to their contribution for segmentation and identifies the most effective ones.
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    Topics: Architecture, Civil Engineering, Surveying , Geography , Geosciences
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