• Journal of Internet of Things and Convergence
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• v.8 no.1
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• pp.53-58
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• 2022

Smoothing is a transmission plan that converts video data stored at a variable bit rate into a constant bit rate. In the study of [6-7], when a data rate increase is required, the frame with the smallest increase is set as the start frame of the next transmission rate section, when a data tate decrease is required. the frame with the largest decrease is set as the start frame of the next transmission rate section, And the smoothing algorithm was proposed and performance was evaluated in an environment where network traffic is not considered. In this paper, the smoothing algorithm of [6-7] evaluates the adaptive CBA algorithm and performance with minimum frame rate, average frame rate, and frame rate variation from 512KB to 32MB with E.T 90 video data in an environment that considers network traffic. As a result of comparison, the smoothing algorithm of [6-7] showed superiority in the comparison of the minimum refresh rate.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.4
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• pp.191-196
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• 2015

In this paper, we present a path-smoothing algorithm for a robot arm manipulator that finds the path using a joint space-based rapidly-exploring random tree. Unlike other smoothing algorithms which require complex mathematical computation, the proposed path-smoothing algorithm is done using a Gaussian process. To find the optimal hyperparameters of the Gaussian process, we use differential evolution hybridized with opposition-based learning. The simulation result indicates that the Gaussian process whose hyperparameters were optimized by hybrid differential evolution successfully smoothed the path generated by the joint space-based rapidly-exploring random tree.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.273-273
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• 2000

We present a new scheme to increase the performance of edge-preserving image smoothing from the parameter tuning of a Markov random field (MRF) function. The method is based on automatic control of the image smoothing-strength in MRF model ing in which an introduced parameter function is based on control of enforcing power of a discontinuity-adaptive Markov function and edge magnitude resulted from discontinuities of image intensity. Without any binary decision for the edge magnitude, adaptive control of the enforcing power with the full edge magnitude could improve the performance of discontinuity-preserving image smoothing.

• Journal of the Korean Institute of Telematics and Electronics
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• v.20 no.6
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• pp.75-80
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• 1983

When an image with spot noise is smoothed by smoothing filters, the noise is almost eliminated However, the image is blurred. The algorithm that reduces such an image blurring is proposed in this paper. In the algorithm, the difference between noisy image and median filtered noisy image is smoothed. As the re-smoothing method, the absolute value of the difference is median filtered and the sign of the difference is affixed on the result. It is shown that the proposed algorithm is quite effective for noise elimination and also for image blurring decrease at the same time. In this paper, the algorithm is compared with the other smoothing methods.

• Journal of radiological science and technology
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• v.47 no.1
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• pp.39-48
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• 2024

In this study, we optimized the FNLM algorithm through a simulation study and applied it to a phantom scanned by low-dose CT to evaluate whether the FNLM algorithm can be used to obtain improved image quality images. We optimized the FNLM algorithm with MASH phantom and FASH phantom, which the algorithm was applied with MATLAB, increasing the smoothing factor from 0.01 to 0.05 with increments of 0.001 and measuring COV, RMSE, and PSNR values of the phantoms. For both phantom, COV and RMSE decreased, and PSNR increased as the smoothing factor increased. Based on the above results, we optimized a smoothing factor value of 0.043 for the FNLM algorithm. Then we applied the optimized FNLM algorithm to low dose lung CT and lung CT under normal conditions. In both images, the COV decreased by 55.33 times and 5.08 times respectively, and we confirmed that the quality of the image of low dose CT applying the optimized FNLM algorithm was 5.08 times better than the image of lung CT under normal conditions. In conclusion, we found that the smoothing factor of 0.043 among the factors of the FNLM algorithm showed the best results and validated the performance by reducing the noise in the low-quality CT images due to low dose with the optimized FNLM algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.11
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• pp.944-952
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• 2001

Inertial navigation system(INS) errors increase with time due to inertial sensor errors, and therefore it is desired to combine INS with external aids such as GPS. However GPS informations have a randomly abrupt jump due to a sudden corruption of the received satellite signals and environment, and moreover GPS can\`t provide navigation solutions. In this paper, smoothing and prediction schemes are proposed for GPS`s jump or unavailable GPS. The smoothing algorithm which is designed as a scalar adaptive filter, smooths abrupt jump. The prediction algorithm which is proved by Schuler error model of INS, estimates INS error in appropriate time. The outputs of proposed algorithm apply stable measurements to GPS aided INS Kalman filter. Simulations show that the proposed algorithm can effectively remove measurement jump and predict INS error.

• MALSORI
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• no.56
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• pp.225-235
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• 2005

Speech unit concatenation with a large database is presently the most popular method for speech synthesis. In this approach, the mismatches at the unit boundaries are unavoidable and become one of the reasons for quality degradation. This paper proposes an algorithm to reduce undesired discontinuities between the subsequent units. Optimal matching points are calculated in two steps. Firstly, the fullback-Leibler distance measurement is utilized for the spectral matching, then the unit sliding and the overlap windowing are used for the waveform matching. The proposed algorithm is implemented for the corpus-based unit concatenating Korean text-to-speech system that has an automatically labeled database. Experimental results show that our algorithm is fairly better than the raw concatenation or the overlap smoothing method.

• Proceedings of the KSRS Conference
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• v.1
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• pp.312-315
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• 2006

Radio occultation technique has been used in planetary science to obtain reliable and accurate temperature profiles of the other planets' atmosphere for decades. It relies on the fact that radio waves are bent and delayed due to the gradient of atmospheric refractivity along-ray-path. With the advent of Global Positioning System (GPS), it becomes possible to retrieve the refractivity and temperature profiles of the Earth's atmosphere from the occultation data. We have developed a retrieval algorithm and compared the results of our algorithm with the data of CHAMP to verify the accuracy of our algorithm is good enough. In our algorithm, there are some smoothing steps when retrieving. We analysis the data of FORMOSAT-3 and compare the results with and without smoothing and the results of TACC to see is there any phenomenon deleted after smoothing.

• International Journal of Naval Architecture and Ocean Engineering
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• v.9 no.5
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• pp.492-498
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• 2017

Subsea pipeline route design is a crucial task for the offshore oil and gas industry, and the route selected can significantly affect the success or failure of an offshore project. Thus, it is essential to design pipeline routes to be eco-friendly, economical and safe. Obstacle avoidance is one of the main problems that affect pipeline route selection. In this study, we propose a technique for designing an automatic obstacle avoidance. The Laplacian smoothing algorithm was used to make automatically generated pipeline routes fairer. The algorithms were fast and the method was shown to be effective and easy to use in a simple set of case studies.

• The Transactions of the Korea Information Processing Society
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• v.7 no.1
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• pp.313-320
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• 2000

PEM algorithm cannot expend repeated algorithm, if penalty function is transcendental function. However, OSL algorithm has an advantage that repeated algorithm is easily derived, even though penalty function which has a complicated transcendental function. In spite of this advantage, this algorithm is restricted in convergence region of smoothing constant which increase penalized log-likelihood, so we cannot get the optimal image restoration because it cannot provide us with a various smoothing constant value for the digital image restoration. In this paper, in order to resolve the disadvantage of OSL algorithm, we would like to suggest the algorithm with smoothing constant enlarge the tolerance limit range of convergence and to find not only properties of its convergence but also usefulness of suggested algorithm through digital image simulation.