• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.3A
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• pp.196-204
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• 2002

The Sinusoidal Transform Coding(STC) is a vocoding scheme based on a sinusoidal model of a speech signal. The low bit-rate speech coding based on sinusoidal model is a method that models and synthesizes speech with fundamental frequency and its harmonic elements, spectral envelope and phase in the frequency region. In this paper, we propose the 2.4kbps low-rate speech coding algorithm using the sinusoidal model of a speech signal. In the proposed coder, the pitch frequency is estimated by choosing the frequency that makes least mean squared error between synthetic speech with all spectrum peaks and speech synthesized with chosen frequency and its harmonics. The spectral envelope is estimated using SEEVOC(Spectral Envelope Estimation VOCoder) algorithm and the discrete all-pole model. The phase information is obtained using the time of pitch pulse occurrence, i.e., the onset time, as well as the phase of the vocal tract system. Experimental results show that the synthetic speech preserves both the formant and phase information of the original speech very well. The performance of the coder has been evaluated in terms of the MOS test based on informal listening tests, and it achieved over the MOS score of 3.1.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.3
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• pp.89-97
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• 2012

In this paper, we propose a novel approach to noise power estimation for speech enhancement in noisy environments. The method based on IMCRA (improved minima controlled recursive averaging) which is widely used in speech enhancement utilizes a rough VAD (voice activity detection) algorithm which excludes speech components during speech periods in order to improves the performance of the noise power estimation by reducing the speech distortion caused by the conventional algorithm based on the minimum power spectrum derived from the noisy speech. However, since the VAD algorithm is not sufficient to distinguish speech from noise at non-stationary noise and low SNRs (signal-to-noise ratios), the speech distortion resulted from the minimum tracking during speech periods still remained. In the proposed method, minimum power estimate obtained by IMCRA is modified by SMT (spectral minima tracking) to reduce the speech distortion derived from the bias of the estimated minimum power. In addition, in order to effectively estimate minimum power by considering the distribution characteristic of the speech and noise spectrum, the presented method combines the minimum estimates provided by IMCRA and SMT depending on the weighting factor based on the subband. Performance of the proposed algorithm is evaluated by subjective and objective quality tests under various environments and better results compared with the conventional method are obtained.

• Geophysics and Geophysical Exploration
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• v.21 no.1
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• pp.54-60
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• 2018

The data acquired from seismic exploration can be used to detect the existence of oil and gas resources through appropriate processing and interpretation. The seismic attributes indicating the existence of resources are extracted from amplitude information, where the Q-factor representing intrinsic attenuation plays an useful role of hydrocarbon indicator. So, the accuracy of Q-factor estimation is very important to investigate the existence of resources. In this study, we calculated the Q-factor and analyzed the error rate through a numerical example. To mimic real data, random noise was added to the synthetic data. With the noise-added data, the Q-factor was estimated and the error rate was analyzed by using the spectral ratio method (SRM) and peak frequency shift method (PFSM). Both methods provided a relatively accurate Q-factor when the signal-to-noise ratio was 90 dB. However, the peak frequency shift method (PFSM) produced better results than the spectral ratio method (SRM) as the level of random noise increased.

• Journal of Navigation and Port Research
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• v.28 no.1
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• pp.97-104
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• 2004

Introduction of wave model, take into account the effect of tide, wind and wave induced currents at the coastal waters of complex bathymetry, is a very important factor for most coastal engineering design and disaster protection problems. As the steady state spectral wave model could simulate depth induced wave shoaling and refraction, current induced refraction effect, steepness induced wave breaking, diffraction, wind wave growth, wave-wave interaction, and wave-current interaction that redistribute energy, this would support and compensate the gap in the real field of design where other wave models could not deal and cause wrong estimation. In this study, for better understanding and analysis of wave transformation process, we applied the spectral wave model to the large coastal waters near Gaduck Island where the Busan new port construction project is going on. We also compared the simulation results with the calculatea from the existing model. From such a trial of this study, we hope that broader and safer use of the spectral model in the area of port design and disaster prevention system come through in near future.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.3
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• pp.3-9
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• 2017

Recently, in 3rd Generation Partnership Project(3GPP), there is a study of the Long Term Evolution(LTE) based vehicle communication which has been actively conducted to provide a transport efficiency, telematics and infortainment. Because the vehicle communication is closely related to the safety, it requires a reliable communication. Because vehicle speed is very fast, unlike the movement of the user, radio channel is rapidly changed and generate a number of problems such as transmission quality degradation. Therefore, we have to continuously updates the channel estimates. There are five types of conventional channel estimation scheme. Least Square(LS) is obtained by pilot symbol which is known to transmitter and receiver. Decision Directed Channel Estimation(DDCE) scheme uses the data signal for channel estimation. Constructed Data Pilot(CDP) scheme uses the correlation characteristic between adjacent two data symbols. Spectral Temporal Averaging(STA) scheme uses the frequency-time domain average of the channel. Smoothing scheme reduces the peak error value of data decision. In this paper, we propose the novel channel estimation scheme in LTE based Vehicle-to-Vehicle(V2V) environment. In our Hybrid Reliable Channel Estimation(HRCE) scheme, DDCE and Smoothing schemes are combined and finally the Linear Minimum Mean Square Error(LMMSE) scheme is applied to minimize the channel estimation error. Therefore it is possible to detect the reliable data. In simulation results, overall performance can be improved in terms of Normalized Mean Square Error(NMSE) and Bit Error Rate(BER).

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.61-73
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• 2014

This study reviewed an application of water quality estimation using an Airborne Hyperspectral Imagery (A-HSI) and tested a part of Han River water quality (especially suspended solid) estimation with available in-situ data. The estimation of water quality was processed two methods. One is using observation data as downwelling radiance to water surface and as scattering and reflectance into water body. Other is linear regression analysis with water quality in-situ measurement and upwelling data as at-sensor radiance (or reflectance). Both methods drive meaningful results of RS estimation. However it has more effects on the auxiliary dataset as water quality in-situ measurement and water body scattering measurement. The test processed a part of Han River located Paldang-dam downstream. We applied linear regression analysis with AISA eagle hyperspectral sensor data and water quality measurement in-situ data. The result of linear regression for a meaningful band combination shows $-24.847+0.013L_{560}$ as 560 nm in radiance (L) with 0.985 R-square. To comparison with Multispectral Imagery (MSI) case, we make simulated Landsat TM by spectral resampling. The regression using MSI shows -55.932 + 33.881 (TM1/TM3) as radiance with 0.968 R-square. Suspended Solid (SS) concentration was about 3.75 mg/l at in-situ data and estimated SS concentration by A-HIS was about 3.65 mg/l, and about 5.85mg/l with MSI with same location. It shows overestimation trends case of estimating using MSI. In order to upgrade value for practical use and to estimate more precisely, it needs that minimizing sun glint effect into whole image, constructing elaborate flight plan considering solar altitude angle, and making good pre-processing and calibration system. We found some limitations and restrictions such as precise atmospheric correction, sample count of water quality measurement, retrieve spectral bands into A-HSI, adequate linear regression model selection, and quantitative calibration/validation method through the literature review and test adopted general methods.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.2
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• pp.139-146
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• 2017

A ground moving target's velocity estimation algorithm applicable for a SAR-GMTI system using 2 channel displaced phase center antenna(DPCA) is proposed. In this algorithm, we assume target's across-track velocity can be estimated by along-track interferometry (ATI) and present a method to estimate target's along-track velocity. To accomplish this method, we first transform a radar-target geometry in which a moving target has zero velocity via altering a radar velocity such that target's velocity is reflected into it and next manipulate the spectral centers of the subapertures within the synthetic aperture. The validity of the proposed algorithm is demonstrated through simulation results showing the performance of the target's velocity estimation and the enhancement of reconstructed target image quality in terms of resolution and SINR.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1537-1549
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• 2020

The ground sample distance of KOMPSAT-3 is 0.7 m for panchromatic band, 2.8 m for multi-spectral band, and the swath width of KOMPSAT-3 is 16 km. Therefore, an image of an area wider than the swath width (16 km) cannot be acquired with a single scanning. Thus, after scanning multiple areas in units of swath width, the acquired images should be made into one image. At this time, the necessary algorithm is called image mosaicking or image stitching, and is used for cartography. Mosaic algorithm generally consists of the following 4 steps: (1) Feature extraction and matching, (2) Radiometric balancing, (3) Seamline estimation, and (4) Image blending. In this paper, we have studied an effective seamline estimation method for satellite images. As a result, we can estimate the seamline more accurately than the existing method, and the heterogeneity of the mosaiced images was minimized.

• The Journal of the Acoustical Society of Korea
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• v.25 no.2
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• pp.78-87
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• 2006

In this paper. we propose an effective mask estimation scheme for missing-feature reconstruction in order to achieve robust speech recognition under unknown noise environments. In the previous work. colored noise is used for training the mask classifer, which is generated from the entire frequency Partitioned signals. However it gives a limited performance under the restricted number of training database. To reflect the spectral events of more various background noise and improve the performance simultaneously. a new Bayesian classifier for mask estimation is proposed, which works independent of other frequency bands. In the proposed method, we employ the colored noise which is obtained by combining colored noises generated from each frequency band in order to reflect more various noise environments and mitigate the 'sparse' database problem. Combined with the cluster-based missing-feature reconstruction. the performance of the proposed method is evaluated on a task of noisy speech recognition. The results show that the proposed method has improved performance compared to the Previous method under white noise. car noise and background music conditions.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.4
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• pp.75-86
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• 2020

The purpose of this study is to develop a technology for estimating rice growth and damage effect according to bacterial leaf blight using UAV multi-spectral imagery. For this purpose, we analyzed the change of aerial images, rice growth factors (plant height, dry weight, LAI) and disease effects according to disease occurrence by using UAV images for 3 rice varieties (Milyang23, Sindongjin-byeo, Saenuri-byeo) from 2017 to 2018. The correlation between vegetation index and rice growth factor during vegetative growth period showed a high value of 0.9 or higher each year. As a result of applying the growth estimation model built in 2017 to 2018, the plant height of Milyang23 showed good error withing 10%. However, it is considered that studies to improve the accuracy of other items are needed. Fixed wing unmanned aerial photographs were also possible to estimate the damage area after 2 to 4 weeks from inoculation. Although sensing data in the multi-spectral (Blue, Green, Red, NIR) band have limitations in early diagnosis of rice disease, for rice varieties such as Milyang23 and Sindongjin-byeo, it was possible to construct the equation of infected leaf area ratio and rice yield estimation using UAV imagery in early and mid-September with high correlation coefficient of 0.8 to 0.9. The results of this study are expected to be useful for farming and policy support related to estimating rice growth, rice plant disease and yield change based on UAV images.