• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2006.05a
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• pp.74-77
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• 2006

A scanned Fabry-Perot(F-P) filter and a Multi-Channel Wavelength Locker(MCWL) were used to interrogate fiber Bragg grating sensor array. When the F-P filter scans over the MCWL which works as a multi-reference the temporal peaks profiles correspond to the locking wavelengths. To solve the linearity, stability, and accuracy problems caused by the nonlinear response of F-P filter, a polynomial fitting algerian was used to calculate the relationship between the peak locations and the wavelengths in all the scanning range. Then from the reflected peaks locations and the best fitting line, the Bragg wavelengths can be obtained. The measurement linearity was greatly enhanced with wavelength resolution of about 4 pm in 10Hz scanning frequency.

• ETRI Journal
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• v.28 no.4
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• pp.509-512
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• 2006

In a real environment, sound recordings are commonly distorted by channel and background noise, and the performance of audio identification is mainly degraded by them. Recently, Philips introduced a robust and efficient audio fingerprinting scheme applying a differential (high-pass filtering) to the frequency-time sequence of the perceptual filter-bank energies. In practice, however, the robustness of the audio fingerprinting scheme is still important in a real environment. In this letter, we introduce alternatives to the frequency-temporal filtering combination for an extension method of Philips' audio fingerprinting scheme to achieve robustness to channel and background noise under the conditions of a real situation. Our experimental results show that the proposed filtering combination improves noise robustness in audio identification.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1995.06a
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• pp.137-141
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• 1995

MASF is a kind of temporal filter proposed for noise reduction and temporal band limitation. MASF uses motion vectors to extract temporal information in spatial domain. Therefore, inaccurate motion information causes some distortions in MASF operation. Currently, bilinear interpolation after MBA(Block Matching Algorithm) is used for the motion estimation sheme of MASF. But, this method results in unreliable estimation when the object in image sequence has larger movement than the maximum displacement assumed in BMA or the input images are severely corrupted with noise. In order to solve this problem, we propose a hierarchical motion estimation algorithm for MASF. Experimental results show that the proposed method produces reliable output under large motion and noisy situations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2866-2880
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• 2014

We propose a video denoising method based on Kalman filter to reduce the noise in video sequences. Firstly, with the strong spatiotemporal correlations of neighboring frames, motion estimation is performed on video frames consisting of previous denoised frames and current noisy frame based on intensity and structure tensor. The current noisy frame is processed in temporal domain by using motion estimation result as the parameter in the Kalman filter, while it is also processed in spatial domain using the Wiener filter. Finally, by weighting the denoised frames from the Kalman and the Wiener filtering, a satisfactory result can be obtained. Experimental results show that the performance of our proposed method is competitive when compared with state-of-the-art video denoising algorithms based on both peak signal-to-noise-ratio and structural similarity evaluations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.5C
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• pp.520-529
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• 2007

In this paper, we study the characteristics of parameters which are related to performance of MCTF which is a key technique for wavelet-based scalable video coding, and propose an improved MCTF method. The proposed MCTF method adopts the motion estimation of which motion vector field is distributed more uniformly using variable block sizes. By using the proposed method, the decomposition performance of temporal filter is improved, and the energy in high-frequency frames is reduced. It can help the entropy coder to generate lower bitrate. From simulation results, we verify the decomposed energy on high-frequency frame using the proposed method is reduced by 25.86% at the most in terms of variance of the high-frequency frame.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.2
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• pp.53-59
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• 2006

Dynamic neural networks have been applied to diverse fields requiring temporal signal processing such as system identification and signal prediction. This paper proposes the gamma neural network(GAM), which uses gamma memory kernel in the hidden layer of feedforward multilayered network, to improve dynamics of networks and then describes nonlinear adaptive prediction using the proposed network as an adaptive filter. The proposed network is evaluated in nonlinear signal prediction and compared with feedforword(FNN) and recurrent neural networks(RNN) for the relative comparison of prediction performance. Simulation results show that the GAM network performs better with respect to the convergence speed and prediction accuracy, indicating that it can be a more effective prediction model than conventional multilayered networks in nonlinear prediction for nonstationary signals.

• Journal of the Korean Society of Visualization
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• v.17 no.3
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• pp.66-69
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• 2019

An image compensating algorithm with high-vibration movement is proposed, using optical flow and the Kalman Filter. The temporal motion vector field is calculated by Optical flow and suspicious vectors are removed or adjusted by the Gaussian interpolation method. The high-vibrated vector filled is stabilized by the Kalman filter. Lastly, compensated images are obtained by affine transformation. This proposed algorithm gives good compensated video images on high-vibration situations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.4
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• pp.706-713
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• 1997

In this paper, we propose a band stop filter(BSF) for reducing drag-like effect of the low pass filter(LPF), a block by block adaptive filtering method, and a motion adaptive filtering method, which show better results in terms of PSNR or human visual perception compared to the conventional method using LPF. The BSF improves the draglike effects of the low pass filter by passing temporal high frequency components of video sequences which correspond to objects with large motion. The proposed adaptive methods also improve the conventional adaptive filtering by modifying the conventional algorithm and applying the algorithms for small blocks. The simulation results show that the proposed filtering methods show better results in terms of PSNR and subjective tests in most cases. Also in case of block by block adaptive filtering, it is verified that the application of the algorithm for smaller block gives better results.

• Journal of Electrical Engineering and information Science
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• v.1 no.1
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• pp.70-76
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• 1996

In this paper, we have proposed a band stop filter (BSF) for pre-processing of image sequences before encoding. By pixel-wise temporal filtering of the image sequences using the BSF, the bandwidth and noise of the signal are reduced, while preserving the image quality in view of human visual perceptions. As a result, when compared to the original image sequences, te pre-filtered image sequence requires lower bit-rates for encoding, while there is not much degradation in quality. Also, it has been shown that the proposed BSF causes less smearing and blurring than the conventional recursive low pass filter for bandwidth and noise reductions.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.2
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• pp.74-80
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• 2008

Spatio-temporal filters are capable of reducing noise from moving pictures, which cannot be dealt with by spatial filters. However, the algorithm is too complicated to be realized as hardware. We implemented a real-time spatio-temporal noise reduction system, using at most three frames, based upon adaptive mean filter algorithm. Some factors which interfere with hardware implementation were modified. Noise estimated from the previous frame was used to filter the current frame so that filtering could be conducted in parallel with noise estimation. This speeds up the system thereby enabling real-time execution. The form of filtering windows was also modified to facilitate synchronization. The proposed structure was implemented on Virtex 4 XC4VLX60, occupying 66% of total slices with 80MHz of the maximum operation frequency.