• Spatial Information Research
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• v.14 no.1 s.36
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• pp.85-94
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• 2006

Image fusion techniques are widely used to integrate a lower spatial resolution multispectral image with a higher spatial resolution panchromatic image. However, the existing techniques either cannot avoid distorting the image spectral properties or involve complicated and time-consuming decomposition and reconstruction processing in the case of wavelet transform-based fusion. In this study a simple spectral preserve fusion technique: the Smoothing Filter-based Replacement(SFR) is proposed based on a simplified solar radiation and land surface reflection model. By using a ratio between a higher resolution image and its low pass filtered (with a smoothing filter) image, spatial details can be injected to a co-registered lower resolution multispectral image minimizing its spectral properties and contrast. The technique can be applied to improve spatial resolution for either colour composites or individual bands. The fidelity to spectral property and the spatial quality of SFM are convincingly demonstrated by an image fusion experiment using IKONOS panchromatic and multispectral images. The visual evaluation and statistical analysis compared with other image fusion techniques confirmed that SFR is a better fusion technique for preserving spectral information.

• ETRI Journal
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• v.26 no.3
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• pp.273-276
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• 2004

We propose a novel feature processing technique which can provide a cepstral liftering effect in the log-spectral domain. Cepstral liftering aims at the equalization of variance of cepstral coefficients for the distance-based speech recognizer, and as a result, provides the robustness for additive noise and speaker variability. However, in the popular hidden Markov model based framework, cepstral liftering has no effect in recognition performance. We derive a filtering method in log-spectral domain corresponding to the cepstral liftering. The proposed method performs a high-pass filtering based on the decorrelation of filter-bank energies. We show that in noisy speech recognition, the proposed method reduces the error rate by 52.7% to conventional feature.

• Korean Journal of Optics and Photonics
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• v.9 no.3
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• pp.151-155
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• 1998

A new Fabry-Perot tunable filter has been built with simple construction, which does not require any additional aligning and/or beam-confining components for the reduction of the diffraction loss. For this feature, one of the two fibers for the filter is processed to have a concave mirror whose curvature is the same as that of the wavefront of the Gaussian beam from the first fiber. After high reflection coatings, the two fibers are aligned to result in an FP filter whose bandwidth, free spectral range, and insertion loss is 1.47nm, 52nm, 5.6dB respectively.

• Journal of the Korean Institute of Telematics and Electronics
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• v.19 no.6
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• pp.55-61
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• 1982

An analytic solution for the spectral response of linearly-chirped grating filter is derived, which takes the finite physical length of filter into account. In the usual case of broad-band linearly-chirped grating filter the analytic solution is expressed in terms of elementary functions, by approximating asymptotically the involved parabolic cylinder functions over different ranges of its argument. It is also shown that derived results are general enough to include previously-available approximations as particular cases, and that they agree well with the numerical solutions based upon the Runge-Kutta method.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.99-100
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• 2008

This paper proposes a Gaussian Mixture Model (GMM) - based speech emotion recognition methods using four feature parameters; 1) Fast Fourier Transform(FFT) spectral entropy, 2) delta FFT spectral entropy, 3) Mel-frequency Filter Bank (MFB) spectral entropy, and 4) delta MFB spectral entropy. In addition, we use four emotions in a speech database including anger, sadness, happiness, and neutrality. We perform speech emotion recognition experiments using each pre-defined emotion and gender. The experimental results show that the proposed emotion recognition using FFT spectral-based entropy and MFB spectral-based entropy performs better than existing emotion recognition based on GMM using energy, Zero Crossing Rate (ZCR), Linear Prediction Coefficient (LPC), and pitch parameters. In experimental Results, we attained a maximum recognition rate of 75.1% when we used MFB spectral entropy and delta MFB spectral entropy.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.30 no.1
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• pp.16-30
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• 1997

Application of digital filter to the wave analysis is studied using the observed data by wave gauge. Sea wave data obtained from wave gauge always include long wave frequency components. In order to estimate the sea wave parameters, we must re-analyzed wave data by using a digital filter and the concept of mean sea level correction method. By the wave by wave analysis and spectral methods, sea wave parameters on the basis of wave data obtained by the conventional method and digital filter are compared. The best-fitted design filter determined by the necessary conditions of frequency responses, can be obtained by calculating various transfer functions. Thus, to get the best the digital filter design, both Butterworth filter and Savitzky-Golay filter of digital filter are used in the frequency and time domain, respectively. Three cases of observation wave data are calculated by applying digital filter. The components of different frequency bands in the surf zone are coexisted in three cases. The wave data for wind wave components is computed using the digital filter the surf zone and off-surf zone, and based on the filtered data, wave parameters are calculated by the spectral analysis and wave by wave analysis methods, respectively. As a results, when sea wave data observed by wave gauge are analyzed, the Savitzky-Golay method is recommended which can well appear cut-off frequency by experimental choosing filter length in the time domain. The better mean sea level correction method is the Butterworth filter in the frequency domain.

• ETRI Journal
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• v.28 no.6
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• pp.770-776
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• 2006

This paper presents a hyperspectral imaging technique based on laser-induced fluorescence for non-invasive detection of tumorous tissue on mouse skin. Hyperspectral imaging sensors collect image data in a number of narrow, adjacent spectral bands. Such high-resolution measurement of spectral information reveals contiguous emission spectra at each image pixel useful for the characterization of constituent materials. The hyperspectral image data used in this study are fluorescence images of mouse skin consisting of 21 spectral bands in the visible spectrum of the wavelengths ranging from 440 nm to 640 nm. Fluorescence signal is measured with the use of laser excitation at 337 nm. An acousto-optic tunable filter (AOTF) is used to capture images at 10 nm intervals. All spectral band images are spatially registered with the reference band image at 490 nm to obtain exact pixel correspondences by compensating the spatial offsets caused by the refraction differences in AOTF at different wavelengths during the image capture procedure. The unique fluorescence spectral signatures demonstrate a good separation to differentiate malignant tumors from normal tissues for rapid detection of skin cancers without biopsy.

• Journal of Biomedical Engineering Research
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• v.15 no.4
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• pp.395-400
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• 1994

High resolution spectral analysis is essential for ECG anaysis. The fast Fourier transform has been widely used for frequency analysis of ECG signals but this procedure provides poor resolution when the data record is short and shows Gibb's phenomena. The ARMA FTF (Fast Transversal Filter) algorithm is used for high resolution spectral analysis. The reason of unsalability of this algorithm is investigated and the method for improving the numerical stability is proposed. The proposed algorithm is applied to spectral analysis of the ECG. Since this result has less variations than the FFT based results, it can be used for the computerized diagonosis of the ECG.

• Journal of the Optical Society of Korea
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• v.16 no.3
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• pp.299-304
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• 2012

A high angular tolerance spectral filter was realized incorporating an etalon, which consists of a $TiO_2$ cavity sandwiched between a pair of Ag/Ge mirrors. The effective angle was substantially extended thanks to the cavity's high refractive index. The device was created by embedding a 313-nm thick $TiO_2$ film in 16-nm thick Ag/Ge films through sputtering, with the Ge layer alleviating the roughness and adhesion of the Ag layer. For normal incidence, the observed center wavelength and transmission were ~900 nm and ~60%, respectively; throughout the range of $50^{\circ}$, the relative wavelength shift and transmission variation amounted to only ~0.06 and ~4%, respectively.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.8
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• pp.761-771
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• 2009

Detecting defects on FPD (Flat Panel Display) color filter before the full panel is made is important to reduce the manufacturing cost. Among many types of defects, the low contrast blemish such as Suzi Mura is difficult to detect using standard CCD cameras. Even skilled inspectors in the inspection line can hardly identify such defects using bare eyes. To overcome this difficulty, point spectrometer has been used to analyze the spectrum to differentiate such defects from normal color filters. However, scanning ever increasing-size color filters by a point spectrometer takes too long time to be used in real production line. We propose a system using a spectral camera which can be viewed as a line scan camera composed of an array of point spectrometers. Three types of lighting system that exhibit different illumination spectrums are devised together with a calibration method of the proposed spectral camera system. To visualize the defect areas, various processing algorithms to identify and to enhance the small differences in spectrum between defective and normal areas are developed. Experiments shows 85% successful visualization. of real samples using the proposed system.