• Proceedings of the KSRS Conference
• /
• 1999.11a
• /
• pp.299-302
• /
• 1999

Generation of a Digital Elevation Model (DEM) in remote sensing is an important application. The process of DEM generation often requires interpolation. This paper is aimed to introduce a class of interpolation algorithms using spectral information, which is widely used in geophysical applications, and to examine the applicability of the method to DEM interpolation. The interpolation process can be explained in two steps. The first step is for finding spectral information from the known data and the second step is finding missing data so as to follow the spectral trend found in the previous step. The interpolation algorithm has been tested for a real DEM data and problems in the DEM interpolation are discussed.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.12 no.5
• /
• pp.968-975
• /
• 1988

The maximum feedrate generated from the hardware DDA is closely related to its calculation efficiency. The smaller interpolation span results in the lower calculation efficiency. This paper presents the method to improve the calculation efficiency for the smaller interpolation span. For the linear interpolation the higher calculation efficiency can be achieved by putting biggest value that the interpolation DDA can hold. for the circular interpolation, however, the scheme used for linear interpolation does not work since arbitrary change of value in the interpolation DDA changes the radius of the circle. The bit length of the hardware DDA is adjusted instead of adjusting the value in DDA, which results in the every same effect on calculation efficiency for the circular interpolation. The hardware circuit and supporting software are designed, and tested by two axis step motor driven milling machine. The experimental results show that the proposed method drastically increases the maximum feedrate even for the smaller interpolation span.

• International Journal of Automotive Technology
• /
• v.8 no.3
• /
• pp.259-268
• /
• 2007

A knock detection circuit that is based on the signal of an accelerometer installed on the engine block of a spark ignition automotive engine has a band-pass filter with a certain frequency as a parameter to be calibrated. A new statistical method for the determination of the frequency which is the most suitable for the knock detection in real-time applications is proposed. The method uses both the cylinder pressure and block vibration signals and is divided into two steps. In both steps, a new recursive trigonometric interpolation method that calculates the frequency contents of the signals is applied. The new trigonometric interpolation method developed in this paper improves the performance of the Discrete Fourier Transformation, allowing a flexible choice of the size of the moving window. In the first step, the frequency contents of the cylinder pressure signal are calculated. The knock is detected in the cylinder of the engine cycle for which at least one value of the maximal amplitudes calculated via the trigonometric interpolation method exceeds a threshold value indicating a considerable amount of oscillations in the pressure signal; this cycle is selected as a knocking cycle. In the second step, the frequency analysis is performed on the block vibration signal for the cycles selected in the previous step. The knock detectability, which is an individual cylinder attribute at a certain frequency, is verified via a statistical hypothesis test for testing the equality of two mean values, i.e. mean values of the amplitudes for knocking and non-knocking cycles. Signal-to-noise ratio is associated in this paper with the value of t-statistic. The frequency with the largest signal-to-noise ratio (the value of t-statistic) is chosen for implementation in the engine knock detection circuit.

• Journal of the Optical Society of Korea
• /
• v.17 no.5
• /
• pp.399-404
• /
• 2013

This article proposes a digital image correlation (DIC) strain measurement method based on a finite element (FE) algorithm. A two-step digital image correlation is presented. In the first step, the gradient-based subpixels technique is used to search the displacements of a region of interest of the specimen, and then the strain fields are obtained by utilizing the finite element method in the second step. Both simulation and experiment processing, including tensile strain deformation, show that the proposed method can achieve nearly the same accuracy as the cubic spline interpolation method in most cases and higher accuracy in some cases, such as the simulations of uniaxial tension with and without noise. The results show that it also has a good noise-robustness. Finally, this method is used in the uniaxial tensile testing for Dahurian Larch wood specimens with or without a hole, and the obtained strain values are close to the results which were obtained from the strain gauge and the cubic spline interpolation method.

• Journal of the Korea Society of Computer and Information
• /
• v.13 no.6
• /
• pp.163-171
• /
• 2008

In this paper, we present an adaptive parametric cubic convolution technique in order to enlarge the low resolution image to the high resolution image. The proposed method consists of two steps. During the first interpolation step, we acquire adaptive parameters in introducing a new cost-function to reflect frequency properties. And, the second interpolation step performs cubic convolution by applying the parameters obtained from the first step. The enhanced interpolation kernel using adaptive parameters produces output image better than the conventional one using a fixed parameter. Experimental results show that the proposed method can not only provides the performances of $0.5{\sim}4dB$ improvements in terms of PSNR, but also exhibit better edge preservation ability and original image similarity than conventional methods in the enlarged images.

• Journal of Broadcast Engineering
• /
• v.18 no.4
• /
• pp.619-630
• /
• 2013

In this paper, we propose an edge directed color demosaicing algorithm considering color channel correlation. The proposed method consists of local region classification step and edge directional interpolation step. In the first step, each region of a given Bayer image is classified as normal edge, pattern edge, and flat regions by using intra channel and inter channel gradients. Especially, two criteria and verification process for the normal edge and pattern edge classification are used to reduce edge direction estimation error, respectively. In the second step, edge directional interpolation process is performed according to characteristics of the classified regions. For horizontal and vertical directional interpolations, missing color components are obtained from interpolation equations based on intra channel and inter channel correlations in order to improve the performance of the directional interpolations. The simulation results show that the proposed algorithm outperforms conventional approaches in both objective and subjective terms.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.18 no.9
• /
• pp.2209-2215
• /
• 2014

This paper presents, a deinterlacing method by improving the Direction-Oriented Interpolation (DOI) technique. The technique is considered to be a very strong tool for intrafield-based deinterlacing. However, DOI has some problems such as long processing time, wrong edge detection in periodic pattern. To remedy this problem, we replace the full search in DOI by a two-step search to reduce processing time and introduces two additional processes to improve image quality. In the proposed method, the spatial direction vectors (SDVs) misread data are reconsidered to prevent them utilizing in the next interpolation step, resulting in an accurate deinterlacing method. We conduct experiments with ISO experimental images to compare the proposed method with the existing methods including line evarage (LA), edge-based line averaging (ELA), DOI, selective deinterlacing algorithm (SDA). Experimental results show the proposed method gives better performance in objective and subjective quality than existing deinterlacing methods.

• Journal of Korea Water Resources Association
• /
• v.43 no.12
• /
• pp.1083-1091
• /
• 2010

Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. However, widely used estimation schemes fail to describe the realistic variability of daily precipitation field. We compare and contrast the performance of statistical methods for the spatial estimation of precipitation in two hydrologically different basins, and propose a two-step process for effective daily precipitation estimation. The methods assessed are: (1) Inverse Distance Weighted Average (IDW); (2) Multiple Linear Regression (MLR); (3) Climatological MLR; and (4) Locally Weighted Polynomial Regression (LWP). In the suggested simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before applying IDW scheme (one of the local scheme) to estimate the amount of precipitation separately on wet days. As the results, the suggested method shows the better performance of daily rainfall interpolation which has spatial differences compared with conventional methods. And this technique can be used for streamflow forecasting and downscaling of atmospheric circulation model effectively.

• Journal of Korea Water Resources Association
• /
• v.44 no.3
• /
• pp.209-220
• /
• 2011

Input uncertainty is one of the major sources of uncertainty in hydrologic modeling. In this paper, first, three alternate rainfall inputs generated by different interpolation schemes were used to see the impact on a distributed watershed model. Later, the residuals of precipitation interpolations were tested as a source of ensemble streamflow generation in two river basins in the U.S. Using the Monte Carlo parameter search, the relationship between input and parameter uncertainty was also categorized to see sensitivity of the parameters to input differences. This analysis is useful not only to find the parameters that need more attention but also to transfer parameters calibrated for station measurement to the simulation using different inputs such as downscaled data from weather generator outputs. Input ensembles that preserves local statistical characteristics are used to generate streamflow ensembles hindcast, and showed that the ensemble sets are capturing the observed steamflow properly. This procedure is especially important to consider input uncertainties in the simulation of streamflow forecast.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.38 no.5
• /
• pp.498-508
• /
• 2001

In this paper, we propose an efficient coding algorithm for the zoom images to find the optimal depth and texture information. The proposed algorithm is the area-based method consisting of two consecutive steps, i) the depth extraction step and ii) the texture extraction step. The X-Y plane of the object space is divided into triangular patches and the depth value of the node is determined in the first step and then the texture of the each patch is extracted in the second step. In the depth extraction step, the depth of the node is determined by applying the block-based disparity compensation method to the windowed area centered at the node. In the second step, the texture of the triangular patches is extracted from the zoom images by applying the affine transformation based disparity compensation method to the triangular patches with the depth value extracted from the first step. To improve the quality of image, the interpolation is peformed on the object space instead of the interpolation on the image plane.