• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.10
• /
• pp.199-203
• /
• 2013

In this paper, a fast algorithm of discrete cosine transform-based interpolation filter (DCT-IF) for HEVC (high efficiency video coding) encoder is proposed. DCT-IF filter accounts for around 30% of encoder complexity, according to the computational complexity analysis with the HEVC reference software. In this work, the proposed DCT-IF is optimized by applying frame-level interpolation, SIMD optimization, and task-level parallelization via OpenMP on a developed C-based HEVC encoder. Performance analysis is conducted by measuring speed-up factor of the proposed optimization technique on the developed encoder. The results show that speed-up factors by frame-level interpolation, SIMD, and OpenMP are approximately 38-46, 3.6-4.4, and 3.0-3.7, respectively. In the end, we achieved the speed-up factor of 498.4 with the proposed fast algorithm.

• The Journal of the Society of Korean Medicine Diagnostics
• /
• v.16 no.1
• /
• pp.9-18
• /
• 2012

Objectives The aim of this study is to propose an optimized tongue colour interpolation method to achieve accurate tongue image rendering. Methods We selected 60 colour chips in the chips of DIC color guide selector, and then divided randomly the colour chips into two groups. The colour chips of a group (Gr I) were used for finding the optimized colour correction factor of error and those of the other group (Gr II) were used for verifying the correction factor. We measured colour value of the Gr I colour chips with spectrophotometer, and took the colour chips image with a digital tongue image system (DTIS). We adjusted colour correction factor of error to equal the chip colour from each method. Through that process, we obtained the optimized colour correction factor. To verify the correction factor, we measured colour value of the Gr II colour chips with a spectrophotometer, and took the colour chips image with the DTIS in the two types of colour interpolation mode (auto white balance mode and optimized colour correction factor mode). And then we calculated the CIE-$L^*ab$ colour difference (${\Delta}E$) between colour values measured with the spectrophotometer and those from images taken with the DTIS. Results In auto white balance mode, The mean ${\Delta}E$ between colour values measured with the spectrophotometer and those from images taken with the DTIS was 13.95. On the other hand, in optimized colour correction factor mode, The mean ${\Delta}E$ was 9.55. The correction rate was over 30%. Conclusions In case of interpolating colour of images taken with the DTIS, we suggest that procedure to search the optimized colour correction factor of error should be done first.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.4A
• /
• pp.677-687
• /
• 2006

Kriging interpolation is one of the generally used interpolation techniques in Geostatistics field. This technique includes the experimental and theoretical variograms and the formulation of kriging interpolation. In contrast to the conventional least square method for stress recovery, kriging interpolation is based on the weighted least square method to obtain the estimated exact solution from the stress data at the Gauss points. The weight factor is determined by variogram modeling for interpolation of stress data apart from the conventional interpolation methods that use an equal weight factor. In addition to this, the p-level is increased non-uniformly or selectively through a posteriori error estimation based on SPR (superconvergent patch recovery) technique, proposed by Zienkiewicz and Zhu, by auto mesh p-refinement. The cut-out plate problem under tension has been tested to validate this approach. It also provides validity of kriging interpolation through comparing to existing least square method.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.48 no.3
• /
• pp.119-124
• /
• 2011

Interpolation filters are widely used in many communication and multimedia applications. Polynomial interpolation computes the coefficients of the polynomial according to the input information to obtain the interpolated value. Recently, FIR interpolation method using supplementary filters was proposed to improve the performances of polynomial interpolation methods. In this paper, by combining a weighting factor approach with the supplementary filter method, we propose a weighted interpolation method which can be efficiently used to compute the maximum or minimum values of a given curve using only a restricted number of sample values. With application to the interpolation of normal distribution curves used in XRF systems, it is shown that the proposed approach exhibits improved performances compared with conventional interpolation methods.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.18 no.3
• /
• pp.706-712
• /
• 2014

This paper describes a determining method of weighting factors for two-point interpolation filters. The interpolation filters is implemented by applying modifying functions to the linear interpolation. Here, there is a problem of determining weights when modifying functions being engaged. The previous method determined the weights by imposing c1-continuity on the interpolation kernels. However, this approach is unable to use the property of individual modifying functions. In this paper, on the basis of spectral analyses of the modifying functions and image signals, we provide a determination method by experimental results. Thus, many experiments are carried out to do so. The results indicate that different weights are required for different modifying functions and also the proposed method outperforms than the previous method.

• Journal of information and communication convergence engineering
• /
• v.9 no.1
• /
• pp.95-99
• /
• 2011

Digital forensics is the emerging research field for determining digital forgeries. Key issues of the tampered images are to solve the problems for detecting the interpolation factor and the tampered regions. This paper describes a method to detect the interpolation factors and the forged maps using the differential method and fast Fourier transform(FFT) along the horizontal, vertical, and diagonal direction, respectively from digital filtered tampered images. The detection map can be used to find out interpolated regions from the tempered image. Experimental results demonstrate the proposed algorithm proves effective on several filtering images by adobe $Photoshop^{TM}$ and show a ratio of detecting the interpolated regions and factors from digital filtered composite images.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.25 no.10A
• /
• pp.1492-1498
• /
• 2000

Pilot symbol aided modulation (PSAM) using the conventional sinc interpolation (CSI) achieves nearly the same BER performance as Caver' optimal Wiener interpolation but with much less complexity. The CSI, however, has to use a non-rectangular window function that is applied to the sinc function to smooth out the abrupt truncation of rectangular window. In this paper, we propose the modified sinc interpolation (MSI). With the weighting factor the MSI scheme with no window has almost the same BER performance as the CSI scheme using window, In addition, if we use the MSI with a window its BER performance gets close to that of the theoretical one. We assume the multicarrier QAM system and an optimal frame structure for performance evaluation.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2015.05a
• /
• pp.427-427
• /
• 2015

The storm water management and drainage relation are the key variable that plays a vital role on hydrological design and risk analysis. These require knowledge about spatial variability over a specified area. Generally, design rainfall values are expressed from the fixed point rainfall, which is depth at a specific location. Concurrently, determine the areal rainfall amount is also very important. Therefore, a spatial rainfall interpolation (point rainfall converting to areal rainfall) can be solved by areal reduction factor (ARF) estimation. In mainland of South Korea, for dam design and its operation, public safety, other surface water projects concerned about ARF for extreme hydrological events. In spite of the long term average rainfall (2,061 mm) and increasing extreme rainfall events, ARF estimation is also essential for Jeju Island's water control structures. To meet up this purpose, five fixed rainfall stations of automatic weather stations (AWS) near the "Hancheon Stream Watershed" area has been considered and more than 50 years of high quality rainfall data have been analyzed for estimating design rainfall. The relationship approach for the 24 hour design storm is assessed based on ARF. Furthermore, this presentation will provide an outline of ARF standards that can be used to assist the decision makers and water resources engineers for other streams of Jeju Island.

• Journal of Multimedia Information System
• /
• v.8 no.4
• /
• pp.203-210
• /
• 2021

Deep leaning convolutional neural networks (CNN) have successfully been applied to image super-resolution (SR). Despite their great performances, SR techniques tend to focus on a certain upscale factor when training a particular model. Algorithms for single model multi-scale networks can easily be constructed if images are upscaled prior to input, but sub-pixel convolution upsampling works differently for each scale factor. Recent SR methods employ multi-scale and multi-path learning as a solution. However, this causes unshared parameters and unbalanced parameter distribution across various scale factors. We present a multi-scale single-path upsample module as a solution by exploiting the advantages of sub-pixel convolution and interpolation algorithms. The proposed model employs sub-pixel convolution for the highest scale factor among the learning upscale factors, and then utilize 1-dimension interpolation, compressing the learned features on the channel axis to match the desired output image size. Experiments are performed for the single-path upsample module, and compared to the multi-path upsample module. Based on the experimental results, the proposed algorithm reduces the upsample module's parameters by 24% and presents slightly to better performance compared to the previous algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.12C
• /
• pp.1184-1193
• /
• 2006

Image interpolation has been widely used and studied in the various fields of image processing. There are many approaches of varying complexity and robustness. In this paper, a new distance weight is proposed for the conventional linear interpolation. In comparison with the conventional linear weight, the new distance weight uses a quadratic or cubic polynomial equation to reflect that the interpolated value should be influenced more by the value of closer pixels in an input image. In this paper, the new adaptive linear (NAL) interpolation, which considers patterns near the interpolated value, is also proposed. This algorithm requires a pattern weight, which is used to determine the ratio of reflection on local patterns, to obtain an interpolated image that exhibits better quality at various magnification factors (MF). In the computer simulation, not only did the NAL interpolation exhibit much lower computational complexity than conventional bicubic interpolation, it also improved peak signal-to-noise ratios (PSNR).