• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.6
• /
• pp.728-735
• /
• 2017

With the proliferation of digital devices, the devices have generated considerable additive white Gaussian noise while acquiring digital images. The most well-known denoising methods focused on eliminating the noise, so detailed components that include image information were removed proportionally while eliminating the image noise. The proposed algorithm provides a method that preserves the details and effectively removes the noise. In this proposed method, the goal is to separate meaningful detail information in image noise environment using the edge strength and edge connectivity. Consequently, even as the noise level increases, it shows denoising results better than the other benchmark methods because proposed method extracts the connected detail component information. In addition, the proposed method effectively eliminated the noise for various noise levels; compared to the benchmark algorithms, the proposed algorithm shows a highly structural similarity index(SSIM) value and peak signal-to-noise ratio(PSNR) value, respectively. As shown the result of high SSIMs, it was confirmed that the SSIMs of the denoising results includes a human visual system(HVS).

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.18 no.5
• /
• pp.91-99
• /
• 2019

Existing node-to-node based optimal path searching is built on the assumption that all destination nodes can be arrived at from an origin node. However, the recent appearance of the adaptive path search algorithm has meant that the optimal path solution cannot be derived in node-to-node path search. In order to reflect transportation data at the links in real-time, the necessity of the node-to-link (or link-to-node; NL) problem is being recognized. This research assumes existence of a network with link-label and non-additive path costs as a solution to the node-to-link optimal path problem. At the intersections in which the link-label has a turn penalty, the network retains its shape. Non-additive path cost requires that M-similar paths be enumerated so that the ideal path can be ascertained. In this, the research proposes direction deletion and turn restriction so that regulation of the loop in the link-label entry-link-based network transformation method will ensure that an optimal solution is derived up until the final link. Using this method on a case study shows that the proposed method derives the optimal solution through learning. The research concludes by bringing to light the necessity of verification in large-scale networks.

• 한국HCI학회:학술대회논문집
• /
• 2009.02a
• /
• pp.178-185
• /
• 2009

A signal processing algorithm is proposed for end point detection which is used commonly in accelerometers-based pattern recognition problem. In the conventional method, end points are detected by manual manipulation with an additive button or algorithm based on statistical computation and highpass filtering to cause critical time delay and difficulty for parameters optimization. As an solution, we propose a focused Time Lagged Feedforward Network(TLFN) with respect to a differential signal of acceleration, which is widely applied for time series forecasting. The simple experiment is conducted with handwriting and the detection performance and response characteristic of the proposed algorithm is tested and analyzed.

• Journal of Electrical Engineering and Technology
• /
• v.10 no.6
• /
• pp.2356-2363
• /
• 2015

Localization of lightning strike point (LSP) in the forest is modeled to mitigate the forest fire damage. Though forest fire ignited by lightning rarely happens, its damage on the forest is grievousness. Therefore, predicting accurate location of LSP becomes crucial in order to control the forest fire. In this paper, we proposed a new hybrid localization algorithm by combining the received signal strength (RSS) and the received signal strength ratio (RSSR) to improve the accuracy by mitigating the environmental effect of lightning strike location in the forest. The proposed hybrid algorithm employs antenna theory (AT) model of cloud-to-ground (CG) return stroke lightning channel to forecast the location of the lightning strike. The obtained results show that the proposed hybrid algorithm achieves better location accuracy compared to the existing RSS method for predicting the lightning strike location considering additive white Gaussian noise (AWGN) environment.

• Journal of Korea Multimedia Society
• /
• v.16 no.12
• /
• pp.1368-1375
• /
• 2013

In this paper, we presents a spatially adaptive noise detection and removal algorithm. Under the assumption that an observed image and the additive noise have Gaussian distribution, the noise parameters are estimated with local statistics, and the parameters are used to define the constraints on the noise detection process, where the first order Markov Random Field (MRF) is used. In addition, an adaptive low-pass filter having a variable window sizes defined by the constraints on noise detection is used to control the degree of smoothness of the reconstructed image. Experimental results demonstrate the capability of the proposed algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2007.06a
• /
• pp.209-212
• /
• 2007

Digital images are corrupted by noises, during signal acquisition and transmission. Amount those noises, additive white Gaussian noise (AWGN) and impulse noise are most representative. The conventional image restoration algorithms are mostly taken in simple noise environment, but they didn't perform very well in tempter noises environment. So a modified image restoration algorithm, which can remove complex noises by using the intensity differences and spatial distances between center pixel and its neighbor pixels as parameters, is proposed in this paper. Simulation results demonstrate that the proposed algorithm can't only remove AWGN and impulse noise separately, but also performs well in preserving details of images as edge.

• Journal of the Korean Data and Information Science Society
• /
• v.20 no.5
• /
• pp.869-878
• /
• 2009

Image restoration techniques such as noise reduction and contrast enhancement have been researched for enhancing a contaminated image by the noise. An image degraded by additive random noise can be enhanced by noise reduction. Sigma filtering is one of the most widely used method to reduce the noise. In this paper, we propose a new sigma filter algorithm based on noise variance estimation which effectively enhances the degraded image by noise. Specifically, the Bartlett test is used to measure the degree of noise with respect to the degree of image feature. Simulation results are also given to show the performance of the proposed algorithm.

• Journal of IKEEE
• /
• v.18 no.4
• /
• pp.523-531
• /
• 2014

In this paper, a fast single image blind denoising algorithm is presented, where noise parameters are estimated by local statistics of an observed degraded image without a prior information about the additive noise. The estimated noise parameters are used to define the constraints on the noise detection which is coupled with the 1st-order Markov Random Field. In addition, an adaptive modified weighted Gaussian filter is introduced, where variable window sizes and weighting coefficients defined by the constraints are used to control the degree of the smoothness of the reconstructed image. The experimental results demonstrate the capability of the proposed algorithm. Please put the abstract of paper here.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
• /
• 2003.11a
• /
• pp.394-397
• /
• 2003

In this paper, we have proposed a clock recovery algorithm of OFDM/QPSK-DMR(Orthogonal Frequency Division Multiplexing/Quadrature Phase Shift Keying Modulation-Digital Microwave Radio)system using BL-PSF(Band Limited-Pulse Shaping Filter) and have analyzed the clock phase error variance performance of OFDM/QPSK and single carrier DMR systems. The existing OFDM/QPSK-DMR system using the windowing requires training sequence or CP(Cyclic Prefix) to synchronize a receiver clock frequency Because there is no training sequence or CP(Cyclic prefix) in our proposed DMR system, the proposed clock recovery algorithm is useful to the OFDM/QPSK-DMR system using BL-PSF, The simulation results confirm that the proposed clock recovery algorithm has the same clock phase error variance performance in a single carrier DMR system under AWGN(Additive White Gaussian Noise) environment.

• Journal of information and communication convergence engineering
• /
• v.4 no.2
• /
• pp.71-74
• /
• 2006

A basic access method about IEEE 802.11 MAC layer protocol using IEEE 802.11 wireless LANs is the DCF thatis based on the CSMA/CA. But, cause of IEEE 802.11 MAC layer uses original backoff algorithm (exponential backoff method), when collision occurred, the size of contention windows increases the double size Also, a time of packet transmission delay increases and efficienty is decreased by original backoff scheme. In this paper, we have analyzed TCP packet transmission time of IEEE 802.11 MAC DCF protocol for wireless LANs a proposed enhanced backoff algorithm. It is considered the transmission time of transmission control protocol (TCP) packet on the orthogonal frequency division multiplexing (OFDM) in additive white gaussian noise (A WGN) and Rician fading channel. From the results, a proposed enhanced backoff algorithm produces a better performance improvement than an original backoff in wireless LAN environment. Also, in OFDM/quadrature phase shift keying channel (QPSK), we can achieve that the transmission time in wireless channel decreases as the TCP packet size increases and based on the data collected, we can infer the correlation between packet size and the transmission time, allowing for an inference of the optimal packet size in the TCP layer.