Spatial PSF Nonuniformity Effects in Airborne Pushbroom Imaging Spectrometry Data

Methods for imputation of missing values in air quality data sets

The ordinary kriging interpolation method is adopted to estimate the 2-D strain tensor elements. The results are then compared with those of the linear and spline interpolation methods. The ordinary kriging method is implemented on 12 GPS permanent stations in South California, collected during 2006 to 2012. By employing these time series, the coordinate changes in the UTM coordinate system can be obtained and the strain tensor elements at these 12 stations can be estimated by means of finite difference method. Interpolation of the strain tensor elements over the study area through these three methods (kriging, spline and linear) indicates that the ordinary kriging results, on average are 70% better than those of the spline and linear interpolation methods.

Restoration of out of focus images is important role in imaging system. The lens defocus may cause image blurring. In this paper, a neural network approach to estimate the blur parameter for uniform out of focus blur is proposed. we estimate the parameter of defocused image in frequency domain by using circle Hough transform, and combine with neural network to have the relationship between the parameter of frequency response of out of focus image and the parameter of uniform out of focus blur model. Finally, we restore the out of focus image with its spatial continuous point spread function (PSF) and the trained neural network. The simulation result shows that the average error with the proposed estimation method is smaller than 0.48%, and more accurate than the existing methods.

Three-dimensional (3D) dynamic contrast-enhanced magnetic resonance imaging (3D DCE-MRI) has been proposed for the assessment of regional perfusion. The aim of this work was the implementation of an algorithm for a 3D parametric visualization of lung perfusion using different cutting planes and volume rendering. Our implementation was based on 3D DCE-MRI data of the lungs of five patients and five healthy volunteers. Using the indicator dilution theory, the regional perfusion parameters, tissue blood flow, blood volume and mean transit time were calculated. Due to the required temporal resolution, the volume elements of dynamic MR data sets show a reduced spatial resolution in the z-direction. Therefore, perfusion parameter volumes were interpolated. Linear interpolation and a combination of linear and nearest-neighbor interpolation were evaluated. Additionally, ray tracing was applied for 3D visualization. The linear interpolation algorithm caused interpolation errors at the lung borders. Using the combined interpolation, visualization of perfusion information in arbitrary cutting planes and in 3D using volume rendering was possible. This facilitated the localization of perfusion deficits compared with the coronal orientated source data. The 3D visualization of perfusion parameters using a combined interpolation algorithm is feasible. Further studies are required to evaluate the additional benefit from the 3D visualization.

Block effect reduction by the 1-D gray polynomial interpolation

Summary A method for mapping soil properties at a regional scale with acceptable precision and cost was investigated. It combines soil classification and interpolation, and uses sample information from a reference area and simple soil observations over the region. The method consists of two stages. First is the prediction of soil properties at a set of sites covering the region by classifying each site according to the soil classification of the reference area, and then by assigning to each site the values of soil properties measured at the representative profile of its soil class. The second is by interpolating the predictions of the properties from the classes at the observation sites. Three methods were considered: kriging, inverse squared distance and nearest neighbour. The performance of classification combined with interpolation was evaluated for mapping water content at wilting point in an area of 1736 ha in a physiographic region of Southern France. The method was compared with conventional methods, namely kriging with actual data and prediction from a soil map at a scale of 1:100000. Estimates from classification combined with kriging were more precise than those from the 1:1OOOOO soil map in all instances, and close to those of ordinary kriging with actual data when prediction points were near the observation points. Classification combined with inverse squared distance or with nearest neighbour interpolation was always less precise than classification with kriging. However, it was more precise than classification at the 1:100 000 scale except when prediction points were far from the observation points.

For the purpose of building a robust AUV controller, which could be used to handle dangerous ocean environment, a method of obtaining benthonic terrain based on Electronic Chart is presented. Firstly, some terrain conversion algorithms for development of the benthonic terrain, such as nearest neighbor interpolation, linear interpolation, cubic interpolation and v4-interpolation are compared; Later a new terrain conversion algorithm for development of the benthonic terrain DTTCGSFD (Delaunay Triangle-based Terrain Considering of Grid, Sparse, Feature Data) is introduced. This method consider the data not only distance constant grid data, Sparse data, but also feature data with the terrain data, such as fathom line etc. In the end, build benthonic terrain making use of Electronic Chart ESRI shapefile database. The result, which is of importance in the AUV research of terrain matching navigation, path planning and obstacle avoidance strategy, has been applied in the research work of our digital AUV platform.

Mathematical formulation of unsmooth surfaces such as the physical earth poses several difficulties. To achieve an accurate formulation, each and every point of the surface must be defined, which is practically impossible. Therefore, in modelling such surfaces there is a need for an adequate number and distribution of reference points as well as an appropriate interpolation method. Working on computerised three-dimensional (3D) models, users can dynamically make various analyses on the surface, one of which is the volume calculation. The accuracy of the volume calculation depends on the appropriateness of the interpolation method used in creating 3D models. The present study, which aims to investigate the accuracy of the calculated volumes of objects with irregular structures, uses an artificial object with irregular form whose volume can be indirectly calculated. Using different interpolation methods on this artificial object through photogrammetrically measured reference points, 3D surface models were formed and volumes were calculated. A comparison between the measured and calculated volume figures revealed that the Inverse Distance Weighting (INDW), Nearest Neighbour (NENE) and Triangulation with Linear (TLIN) interpolation methods yielded more accurate results than the other methods. In order to investigate the volumetric accuracy, the same procedure was applied to a regular geometrically-shaped conical frustum and a pyramidal frustum with different numbers of faces, whose reference points on the surface were reproduced in accordance with mathematical rules. The volume of the pyramidal frustum which was obtained using different interpolation methods was then compared to that of the pyramidal frustum which was mathematically calculated and that of the conical frustum which was taken as the reference surface. The comparison demonstrated that the Data Metrics (DMET), INDW and Minimum Curvature (MCRV) interpolation methods yielded better results in terms of volumetric accuracy. Keywords: Interpolation methods, DTM, landform volume, volumetric accuracy.

Traditional k-nearest neighbor methods couldn’t be able to correctly classify objects when their k nearest neighbors are dominated by other classes. This paper formulates a two-class classification problem, and applies a modified k-nearest neighbors (KNN) classifier algorithm based on maximal coherence, validity ratings, and k-fold cross validation to classify the test samples. We build a validity score for the pairs of sample and their surroundings according to their labels. The k nearest neighbors (including the unknown test object) of each sample in the training set as well as the unknown test object itself will be determined. The unknown test object will be tentatively assigned to a class membership. Then we use the validity scores to quantify the degree to which a pre-determined group of samples resemble their k nearest neighbors. A classifier is designed which take into account the coherence and validity ratings. A numerical example demonstrates the effectiveness of the algorithm in detail. The enhanced KNN method is compared with the conventional KNN and the modified KNN method on both real world wine data and photo-thermal infrared imaging spectroscopy (PT-IRIS) data for up to 20 different k values. Classification accuracy of KNN method and our method in terms of various combinations of k-value and k-fold cross validation are compared. The experimental results show that the proposed enhanced KNN method outperforms the conventional KNN and the modified KNN method on both real world wine data and PT-IRIS data. In addition, the classification accuracy of both the conventional KNN and our method increase drastically when k = 5. The average classification accuracy of our method on the PT-IRIS data featuring small sample size and high overlap is 97.87%.

The purpose of this study is to quantitatively analyze the effect of an ectopic beat on heart rate variability (HRV) in the time domain, frequency domain, and in a non-linear analysis. A quantitative analysis was carried out by generating artificial ectopic beats that probabilistically contained a missed beat or a false-detected beat, and the statistical significance was evaluated though a comparison with an ectopic-free HRV by increasing the ratio of the ectopic beat in 0.1% increments from 0 to 50%. The effect of the interpolation on the ectopic HRV was also investigated by applying nearest-neighbor interpolation, linear interpolation, and cubic spline interpolation. The results confirmed a statistically significant difference (P < 0.05) even in the less-than-1% ectopic HRV in every domain. When interpolation was applied, there were differences according to the interpolation method used, but statistical significance was secured for an ectopic beat ratio from 1 to 2% to several tens of a percent. In the effect, linear interpolation, and spline interpolation were confirmed to have a higher effect on the high-frequency related HRV variables, and nearest-neighbor interpolation had a higher effect on low-frequency related variables.

The article is devoted to the issue of definition in situ vertical effective stress in weakly filtering soils (WFS). Shown. that the calculation of the vertical effective stress in soils, taking into account the weighing action of water, is valid only for the special case of the hydrostatic distribution of pore pressure over depth. In this regard, it is proposed to determine the vertical effective stress by the difference between total and pore pressure, in accordance with the principle of effective stresses of K. Terzagi, as more universal. The existing variants of pore pressure calculations in weakly filtering soils are considered. The example shows that zeroing the pore pressure leads to an overestimation of the in situ effective stress in the WFS, and the hydrostatic distribution, as a rule, leads to its underestimation. A computational method for determining the vertical effective stress in the WFS by linear interpolation is presented. Formulas for determining pore pressure and vertical effective stress in the WFS layer are proposed. The features of the application of the interpolation method for different values of groundwater levels in aquifers in depth are considered. A necessary condition for calculating the pore pressure by interpolation is information about the level of groundwater in the underlying aquifer, which must be taken into account when performing engineering-geological surveys. Examples of comparison of the results obtained by various calculation methods with the data of direct measurements of pore pressure by the dissipation method and the method of filled wells are given. The analysis showed that the values of pore pressure in the WFS layers calculated by linear interpolation correspond to direct measurements of pore pressure to the greatest extent. Thus, the linear interpolation method is the most reliable calculation method and can be recommended for use when performing geotechnical calculations.

Sparse-view tomography has many applications such as in low-dose computed tomography (CT). Using under-sampled data, a perfect image is not expected. The goal of this paper is to obtain a tomographic image that is better than the naïve filtered backprojection (FBP) reconstruction that uses linear interpolation to complete the measurements. This paper proposes a method to estimate the un-measured projections by displacement function interpolation. Displacement function estimation is a non-linear procedure and the linear interpolation is performed on the displacement function (instead of, on the sinogram itself). As a result, the estimated measurements are not the linear transformation of the measured data. The proposed method is compared with the linear interpolation methods, and the proposed method shows superior performance.

Processing an image is a process and image analysis which entangling many visual perceptions and in course have some characteristics of input data and output information in binding digital image. Process of changing measure for an image through magnification of resolution or measure often needed to showing the detail, for demonstration at a physic appliance, and for making of document. At the process on enlarging image resolution, method that would be used in this paper is linear interpolation. Linear Interpolation Method is mathematics algorithm which could be applied to appraise the middle price point through a diametrical line, two successive input point. The system in this paper could process image with algorithm of linear interpolation and become a new photo image with image resolution of pixel larger than the original image.Keywords: image, resolution, linear, interpolation, pixel

One critical issue in network real-time kinematic (NRTK) is the interpolation of atmospheric delay for user stations. Some classic interpolation algorithms, such as linear interpolation method (LIM), ignore the strong correlation between tropospheric delay and height factors, and the interpolation accuracy is poor in areas with large height difference. To solve this problem, a troposphere modelling method based on error compensation, namely ECDIM (Error Compensation-Based DIM), is proposed, and this method can be applied to both conventional single Delaunay triangulated network (DTN) and multi-station scenarios. The results of California Real Time Network (CRTN) with large height difference show that compared with LIM, the overall modelling accuracy with ECDIM has been improved by 50.1% to 67.3%, and especially for low elevation satellites (e.g., 10–20 degree), the accuracy is increased from tens of centimetres to a few centimetres. At user end, the positioning error in up direction with LIM has an obvious systematic deviation, and the fix rate of epoch is relatively low. This situation has been improved significantly after using ECDIM. The results of Tianjin Continuously Operating Reference System (TJCORS) show that in areas with small height difference, both methods have achieved high precision interpolation accuracy, and the positioning accuracy with ECDIM in up direction is improved by 21.2% compared with LIM.

Predicting glass transition temperature of polymers by combining molecular dynamics simulations and machine learning techniques