The nanocaps array of TiO₂/Ag bilayer with different Ag thicknesses and co-sputtering TiO₂-Ag monolayer with different TiO₂ contents were fabricated on a two-dimensional colloidal array substrate for the investigation of Surface enhanced Raman scattering (SERS) properties. For the TiO₂/Ag bilayer, when the Ag thickness increased, SERS intensity decreased. Meanwhile, a significant enhancement was observed when the sublayer Ag was 10 nm compared to the pure Ag monolayer, which was ascribed to the metal-semiconductor synergistic effect that electromagnetic mechanism (EM) provided by roughness surface and charge-transfer (CT) enhancement mechanism from TiO₂-Ag composite components. In comparison to the TiO₂/Ag bilayer, the co-sputtered TiO₂-Ag monolayer decreased the aggregation of Ag particles and led to the formation of small Ag particles, which showed that TiO₂ could effectively inhibit the aggregation and growth of Ag nanoparticles. Full article

In deepwater oil and gas drilling, the high-molecular-weight encapsulator aggravates the thickening of the drilling fluid at low temperatures. Therefore, it is hard to manage the downhole pressure, and drilling fluid loss occurs. In this paper, a zwitterionic polymer P(AM-DMC-AMPS) which was the terpolymer of acrylamide, methacrylatoethyl trimethyl ammonium chloride, and 2-acrylamido-2-methylpropane sulfonic acid, was developed as a low-molecular-weight encapsulator. It was characterized by Fourier transform infrared spectrum analysis, nuclear magnetic resonance, and gel permeation chromatography. Moreover, the low-temperature rheology, shale inhibition and filtration properties of water-based drilling fluids (WBDFs) containing different encapsulators were experimentally investigated and compared. The results showed that the molecular weight of P(AM-DMC-AMPS) was about 260,000, much lower than that of the conventional encapsulators. In the deepwater drilling temperature range 4–75 °C, WBDF containing P(AM-DMC-AMPS) had lower and more stable rheological property because of its short molecular chains. The high shale recovery rate and low swelling rate indicated its strong shale inhibition performance, owing to its adsorption on the clay surface and the wrapping effect through both hydrogen bonding and electrostatic interaction. It also improved the filtration property of WBDF, and was compatible with other WBDF components. This product is expected to simultaneously realize the good encapsulation performance and low-temperature rheological property for deepwater drilling fluid. Full article

As the core issue for Digital Surface Model (DSM) generation, image matching is often implemented in photo space to get disparity or depth map. However, DSM is generated in object space with additional processes such as reference image selection, disparity maps fusion or depth maps merging, and interpolation. This difference between photo space and object space leads to process complexity and computation redundancy. We propose a direct DSM generation approach called the semi-global vertical line locus matching (SGVLL), to generate DSM with dense matching in the object space directly. First, we designed a cost function, robust to the pre-set elevation step and projection distortion, and detected occlusion during cost calculation to achieve a sound photo-consistency measurement. Then, we proposed an improved semi-global cost aggregation with guidance of true-orthophoto to obtain superior results at weak texture regions and slanted planes. The proposed method achieves performance very close to the state-of-the-art with less time consumption, which was experimentally evaluated and verified using nadir aerial images and reference data. Full article

Automatic cloud extraction from satellite imagery is a vital process for many applications in optical remote sensing since clouds can locally obscure the surface features and alter the reflectance. Clouds can be easily distinguished by the human eyes in satellite imagery via remarkable regional characteristics, but finding a way to automatically detect various kinds of clouds by computer programs to speed up the processing efficiency remains a challenge. This paper introduces a new cloud detection method based on probabilistic latent semantic analysis (PLSA) and object-based machine learning. The method begins by segmenting satellite images into superpixels by Simple Linear Iterative Clustering (SLIC) algorithm while also extracting the spectral, texture, frequency and line segment features. Then, the implicit information in each superpixel is extracted from the feature histogram through the PLSA model by which the descriptor of each superpixel can be computed to form a feature vector for classification. Thereafter, the cloud mask is extracted by optimal thresholding and applying the Support Vector Machine (SVM) algorithm at the superpixel level. The GrabCut algorithm is then applied to extract more accurate cloud regions at the pixel level by assuming the cloud mask as the prior knowledge. When compared to different cloud detection methods in the literature, the overall accuracy of the proposed cloud detection method was up to 90 percent for ZY-3 and GF-1 images, which is about a 6.8 percent improvement over the traditional spectral-based methods. The experimental results show that the proposed method can automatically and accurately detect clouds using the multispectral information of the available four bands. Full article

With the urgent demand for automatic management of large numbers of high-resolution remote sensing images, content-based high-resolution remote sensing image retrieval (CB-HRRS-IR) has attracted much research interest. Accordingly, this paper proposes a novel high-resolution remote sensing image retrieval approach via multiple feature representation and collaborative affinity metric fusion (IRMFRCAMF). In IRMFRCAMF, we design four unsupervised convolutional neural networks with different layers to generate four types of unsupervised features from the fine level to the coarse level. In addition to these four types of unsupervised features, we also implement four traditional feature descriptors, including local binary pattern (LBP), gray level co-occurrence (GLCM), maximal response 8 (MR8), and scale-invariant feature transform (SIFT). In order to fully incorporate the complementary information among multiple features of one image and the mutual information across auxiliary images in the image dataset, this paper advocates collaborative affinity metric fusion to measure the similarity between images. The performance evaluation of high-resolution remote sensing image retrieval is implemented on two public datasets, the UC Merced (UCM) dataset and the Wuhan University (WH) dataset. Large numbers of experiments show that our proposed IRMFRCAMF can significantly outperform the state-of-the-art approaches. Full article

This paper presents a novel image matching method for multi-source satellite images, which integrates global Shuttle Radar Topography Mission (SRTM) data and image segmentation to achieve robust and numerous correspondences. This method first generates the epipolar lines as a geometric constraint assisted by global SRTM data, after which the seed points are selected and matched. To produce more reliable matching results, a region segmentation-based matching propagation is proposed in this paper, whereby the region segmentations are extracted by image segmentation and are considered to be a spatial constraint. Moreover, a similarity measure integrating Distance, Angle and Normalized Cross-Correlation (DANCC), which considers geometric similarity and radiometric similarity, is introduced to find the optimal correspondences. Experiments using typical satellite images acquired from Resources Satellite-3 (ZY-3), Mapping Satellite-1, SPOT-5 and Google Earth demonstrated that the proposed method is able to produce reliable and accurate matching results. Full article

The paper presents an automatic region detection based method to reconstruct street scenes from driving recorder images. The driving recorder in this paper is a dashboard camera that collects images while the motor vehicle is moving. An enormous number of moving vehicles are included in the collected data because the typical recorders are often mounted in the front of moving vehicles and face the forward direction, which can make matching points on vehicles and guardrails unreliable. Believing that utilizing these image data can reduce street scene reconstruction and updating costs because of their low price, wide use, and extensive shooting coverage, we therefore proposed a new method, which is called the Mask automatic detecting method, to improve the structure results from the motion reconstruction. Note that we define vehicle and guardrail regions as “mask” in this paper since the features on them should be masked out to avoid poor matches. After removing the feature points in our new method, the camera poses and sparse 3D points that are reconstructed with the remaining matches. Our contrast experiments with the typical pipeline of structure from motion (SfM) reconstruction methods, such as Photosynth and VisualSFM, demonstrated that the Mask decreased the root-mean-square error (RMSE) of the pairwise matching results, which led to more accurate recovering results from the camera-relative poses. Removing features from the Mask also increased the accuracy of point clouds by nearly 30%–40% and corrected the problems of the typical methods on repeatedly reconstructing several buildings when there was only one target building. Full article

A community-based intervention study was conducted to assess a nutrition education intervention on western style fast food consumption among Chinese children and parents. Eight kindergartens from three district areas of Hefei City (a total of 1252 children aged 4–6 years and their parents) were randomly selected. Descriptive and analytical statistical methods were used to evaluate the baseline, midterm, and final western style fast food knowledge, attitude, and practice in both parents and children were used to identify and compare the knowledge, attitude, and practice in the parents and children. Parents and children were divided into “intervention” and “control” groups based on nutrition education status. Consumption of western style fast food at breakfast in Chinese children and parents is not high. The main reasons for this in children is that consumption of western style fast food is not viewed as “food”, but rather as a “gift” or “interesting”. The time of children’s consumption of western style fast food is mostly likely to be in the weekends. The nutrition education modified the parents’ western style fast food behavior (p < 0.01), although it did not change significantly in children. The healthy nutrition concept should be built up among Chinese, especially in children. Insights from the families provide leads for future research and ideas for the nutrition education. Full article

In the midst of the rapid developments in electronic instruments and remote sensing technologies, airborne three-line array sensors and their applications are being widely promoted and plentiful research related to data processing and high precision geo-referencing technologies is under way. The exterior orientation parameters (EOPs), which are measured by the integrated positioning and orientation system (POS) of airborne three-line sensors, however, have inevitable systematic errors, so the level of precision of direct geo-referencing is not sufficiently accurate for surveying and mapping applications. Consequently, a few ground control points are necessary to refine the exterior orientation parameters, and this paper will discuss bundle block adjustment models based on the systematic error compensation and the orientation image, considering the principle of an image sensor and the characteristics of the integrated POS. Unlike the models available in the literature, which mainly use a quaternion to represent the rotation matrix of exterior orientation, three rotation angles are directly used in order to effectively model and eliminate the systematic errors of the POS observations. Very good experimental results have been achieved with several real datasets that verify the correctness and effectiveness of the proposed adjustment models. Full article