• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.11a
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• pp.23-29
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• 2003

Detection in remotely sensed images can be conducted spatially, spectrally or both [2]. If the images have high spatial resolution, materials can be detected by using spatial and spectral information, unless we can't see the object embedded in a pixel. In this paper, we intend to solve the limit of spatial resolution by using the hyperspectral image which has high spectral resolution. Therefore, the Linear Spectral Mixing(LSM) Model which is sub-pixel detection algorithm is used to solve this problem. To find class Endmembers, we applied Geometric Model with MNF(Minimum Noise Fraction) transformation. From the result of sub-pixel detection algorithm, we can see the detection of water is satisfied and the object shape cannot be extracted but the possibility of material existence can be identified.

• Korean Journal of Remote Sensing
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• v.21 no.5
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• pp.405-415
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• 2005

It is difficult to classify tidal flat surface that is composed of a mixture of mud, sand, water and microphytobenthos. We used a Linear Spectral Unmixing (LSU) method for effectively classifying the tidal flat surface characteristics within a pixel. This study aims at 1) detecting algal mat using LSU in the Saemangeum tidal flats, 2) determining a suitable end-member selection method in tidal flats, and 3) find out a habitual characteristics of algal mat. Two types of end-member were built; one is a reference end-member derived from field spectrometer measurements and the other image end-member. A field spectrometer was used to measure spectral reflectance, and a spectral library was accomplished by shape difference of spectra, r.m.s. difference of spectra, continuum removal and Mann-Whitney U-test. Reference end-members were extracted from the spectral library. Image end-members were obtained by applying Principle Component Analysis (PCA) to an image. The LSU method was effective to detect microphytobenthos, and successfully classified the intertidal zone into algal mat, sediment, and water body components. The reference end-member was slightly more effective than the image end-member for the classification. Fine grained upper tidal flat is generally considered as a rich habitat for algal mat. We also identified unusual microphytobenthos that inhabited coarse grained lower tidal flats.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.3
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• pp.211-218
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• 2015

The analysis of remote sensing data depends on sensor specifications that provide accurate and consistent measurements. However, it is not easy to establish confidence and consistency in data that are analyzed by different sensors using various radiometric scales. For this reason, the cross-calibration method is used to calibrate remote sensing data with reference image data. In this study, we used an airborne hyperspectral image in order to calibrate a multispectral image. We presented an automatic cross-calibration method to calibrate a multispectral image using hyperspectral data and spectral mixture analysis. The spectral characteristics of the multispectral image were adjusted by linear regression analysis. Optimal endmember sets between two images were estimated by spectral mixture analysis for the linear regression analysis, and bands of hyperspectral image were aggregated based on the spectral response function of the two images. The results were evaluated by comparing the Root Mean Square Error (RMSE), the Spectral Angle Mapper (SAM), and average percentage differences. The results of this study showed that the proposed method corrected the spectral information in the multispectral data by using hyperspectral data, and its performance was similar to the manual cross-calibration. The proposed method demonstrated the possibility of automatic cross-calibration based on spectral mixture analysis.

• Journal of Ship and Ocean Technology
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• v.9 no.4
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• pp.11-22
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• 2005

This paper addresses details of wave load nonlinearity effect on stress RAO and damage ratio using component stochastic fatigue analysis. Traditional spectral fatigue analysis for ship structure is based on linear theory; however, there are a number of nonlinearity sources. Especially loading nonlinearity, such as hydrodynamic pressure applying to ship side and gravity changes due to roll and pitch motion, is thought to critically violate the linearity assumption of spectral fatigue analysis, which involves stress RAO as linear parameter. The main focus is placed on how to idealize complicated characteristics of loading nonlinearity and how to implement the nonlinear bias to linear spectral fatigue analysis.

• Proceedings of the Korean Printing Society Conference
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• 2000.04a
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• pp.35-44
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• 2000

Because Image on the CRT change under different illuminants, human is difficult to see original color of object. If what is information of used illuminant on capturing object know, image can be transformed according to viewing condition using the linear matrix method. To know information of used illuminant at an image, the spectral radiance of illuminant can be estimated using the linear model of Maloney and Wandell form an image. And then image can be properly transformed it using color appearance model. In this paper, we predict the spectral radiance of illuminant using spectral power distribution of specular light and using surface spectral reflectance at maximum gray area. and then we perform visual experiments for the corresponding color reproduction according to viewing condition. In results, we ensure that the spectral radiance of illuminant at an image can be well estimated using above algorithms and that human visual system is 70% adapted to the monitor's white point and 30% to ambient light when viewing softcopy images.

• Journal of the Chungcheong Mathematical Society
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• v.16 no.1
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• pp.37-48
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• 2003

In this paper, we show that for a pure hyponormal operator the analytic spectral subspace and the algebraic spectral subspace are coincide. Using this result, we have the following result: Let T be a decomposable operator on a Banach space X and let S be a pure hyponormal operator on a Hilbert space H. Then every linear operator ${\theta}:X{\rightarrow}H$ with $S{\theta}={\theta}T$ is automatically continuous.

• Journal of the Korean Mathematical Society
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• v.40 no.2
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• pp.307-317
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• 2003

For linear operators between Banach algebras "spectral boundedness" is derived from ordinary boundedness by substituting spectral radius for norm. The interplay between this concept and some of its near relatives is conspicuous in a result of Curto and Mathieu.

• Journal of the Chungcheong Mathematical Society
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• v.29 no.4
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• pp.677-686
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• 2016

Algebraic spectral subspaces were introduced by Johnson and Sinclair via a transnite sequence of spaces. Laursen simplified the definition of algebraic spectral subspace. Algebraic spectral subspaces are useful in automatic continuity theory of intertwining linear operators on Banach spaces. In this paper, we characterize algebraic spectral subspaces of operators with finite ascent. From this characterization we show that if T is a generalized scalar operator, then T has finite ascent.

• Sleep Medicine and Psychophysiology
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• v.15 no.1
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• pp.5-11
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• 2008

Sleep is an essential process maintaining the life cycle of the human. In parallel with physiological, cognitive, subjective, and behavioral changes that take place during the sleep, there are remarkable changes in the electroencephalogram (EEG) that reflect the underlying electro-physiological activity of the brain. However, analyzing EEG and relating the results to clinical observations is often very hard due to the complexity and a huge data amount. In this article, I introduce several linear and non-linear tools, developed to analyze a huge time series data in many scientific researches, and apply them to EEG to characterize various sleep states. In particular, the spectral analysis, detrended fluctuation analysis (DFA), and synchrony analysis are administered to EEG recorded during nocturnal polysomnography (NPSG) processes and daytime multiple sleep latency tests (MSLT). I report that 1) sleep stages could be differentiated by the spectral analysis and the DFA ; 2) the gradual transition from Wake to Sleep during the sleep onset could be illustrated by the spectral analysis and the DFA ; 3) electrophysiological properties of narcolepsy could be characterized by the DFA ; 4) hypnic jerks (sleep starts) could be quantified by the synchrony analysis.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.853-855
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• 2003

Microphytobenthos that supply nutrients to the intertidal ecosystem play an important part as a primary producer. If we estimate distribution and density of microphytobenthos, we can possibly calculate a volume of primary product in the tidal flat and its effect to the intertidal ecosystem. To estimate the portion of microphytobenthos, we used a linear spectral unmixing (LSU) method. LSU is a tool for inference the proportions of the pure components (or end-members) in a mixed pixel. The selection of end-members is critical to LSU. The end-members can be selected either from spectral libraries built from field surveys or from a remotely sensed image. We compared the two approaches of end-member selection, and the preliminary results showed end-members from from spectral library are as effective as those from image itself.