• Korean Journal of Remote Sensing
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• v.26 no.3
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• pp.325-333
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• 2010

Image registration involves overlapping images of an identical region and assigning the data into one coordinate system. Image registration has proved important in remote sensing, enabling registered satellite imagery to be used in various applications such as image fusion, change detection and the generation of digital maps. The image descriptor, which extracts matching points from each image, is necessary for automatic registration of remotely sensed data. Using contrast enhancement algorithms such as histogram equalization and image stretching, the normalized data are applied to the image descriptor. Drawing on the different spectral characteristics of high resolution satellite imagery based on sensor type and acquisition date, the applied normalization method can be used to change the results of matching interest point descriptors. In this paper, the matching points by scale invariant feature transformation (SIFT) are extracted using various contrast enhancement algorithms and injection of Gaussian noise. The results of the extracted matching points are compared with the number of correct matching points and matching rates for each point.

• The Journal of the Acoustical Society of Korea
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• v.33 no.1
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• pp.81-86
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• 2014

This paper presents a study on the effectiveness of using the spectral and the temporal octave-band order statistics for musical genre classification. In order to represent the relative disposition of the harmonic and non-harmonic components, we utilize the octave-band order statistics of power spectral distribution. Experiments on the widely used two music datasets were performed; the results show that the octave-band order statistics improve genre classification accuracy by 2.61 % for one dataset and 8.9 % for another dataset compared with the mel-frequency cepstral coefficients and the octave-band spectral contrast. Experimental results show that the octave-band order statistics are promising for musical genre classification.

• 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.

• Journal of Astronomy and Space Sciences
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• v.13 no.2
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• pp.198-209
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• 1996

In this paper, we present an image compression algorithm that is capable of significantly reducing the vast mount of information contained in multispectral images. The developed algorithm exploits the spectral and spatial correlations found in multispectral images. The scheme encodes the difference between images after contrast/brightness equalization to remove the spectral redundancy, and utilizes a two-dimensional wavelet trans-form to remove the spatial redundancy. The transformed images are than encoded by hilbert-curve scanning and run-length-encoding, followed by huffman coding. We also present the performance of the proposed algorithm with KITSAT-1 image as well as the LANDSAT MultiSpectral Scanner data. The loss of information is evaluated by peak signal to noise ratio (PSNR) and classification capability.

• Korean Journal of Radiology
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• v.21 no.7
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• pp.838-850
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• 2020

Computed tomography (CT) is an important imaging modality in evaluating thoracic malignancies. The clinical utility of dual-energy spectral computed tomography (DESCT) has recently been realized. DESCT allows for virtual monoenergetic or monochromatic imaging, virtual non-contrast or unenhanced imaging, iodine concentration measurement, and effective atomic number (Z_eff map). The application of information gained using this technique in the field of thoracic oncology is important, and therefore many studies have been conducted to explore the use of DESCT in the evaluation and management of thoracic malignancies. Here we summarize and review recent DESCT studies on clinical applications related to thoracic oncology.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.03a
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• pp.493-498
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• 2004

The objective of the present study is to compare various conventional and recently evolved satellite image-processing techniques and to ascertain the best possible technique that can identify and position of aquaculture farms accurately in and around the Younggwang coastal area. Several conventional techniques performed to extract such information fiom the Landsat-TM imagery do not seem to yield better information about the aquaculture farms, and lead to misclassification. The large errors between the actual and extracted aquaculture farm information are due to existence of spectral confusion and inadequate spatial resolution of the sensor. This leads to possible occurrence of mixture pixels or 'mixels' of the source of errors in the classification techniques. Understanding the confusing and mixture pixel problems requires the development of efficient methods that can enable more reliable extraction of aquaculture farm information. Thus, the more recently evolved methods such as the step-by-step partial spectral end-member extraction and linear spectral unmixing methods are introduced. The farmer one assumes that an end-member, which is often referred to as 'spectrally pure signature' of a target feature, does not appear to be a spectrally pure form, but always mix with the other features at certain proportions. The assumption of the linear spectral unmxing is that the measured reflectance of a pixel is the linear sum of the reflectance of the mixture components that make up that pixel. The classification accuracy of the step-by-step partial end-member extraction improved significantly compared to that obtained from the traditional supervised classifiers. However, this method did not distinguish the aquaculture ponds and non-aquaculture ponds within the region of the aquaculture farming areas. In contrast, the linear spectral unmixing model produced a set of fraction images for the aquaculture, water and soil. Of these, the aquaculture fraction yields good estimates about the proportion of the aquaculture farm in each pixel. The acquired proportion was compared with the values of NDVI and both are positively correlated (R$^2$ =0.91), indicating the reliability of the sub-pixel classification.ixel classification.

• Bulletin of the Korean Chemical Society
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• v.34 no.7
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• pp.2143-2147
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• 2013

Matrix assisted laser desorption/ionization (MALDI) mass spectrometry (MS) is a very effective method for lipid mass fingerprinting. However, MALDI MS suffered from spectral complexities, differential ionization efficiencies, and poor reproducibility when analyzing complex lipid mixtures without prior separation steps. Here, we aimed to find optimal MALDI sample preparation methods which enable selective or class-wide mass fingerprinting of two totally different lipid classes. In order to achieve this, various matrices with additives were tested against the mixture of phosphatidylcholine (PC) and cerebrosides (Cers) which are abundant in animal brain tissues and also of great interests in disease biology. Our results showed that, from complex lipid mixtures, 2,4,6-trihydroxyacetophenone (THAP) with $NaNO_3$ was a useful MALDI matrix for the class-wide fingerprinting of PC and Cers. In contrast, THAP efficiently generated PC-focused profiles and graphene oxide (GO) with $NaNO_3$ provided Cer-only profiles with reduced spectral complexity.

• Communications for Statistical Applications and Methods
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• v.24 no.1
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• pp.1-13
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• 2017

This manuscript summarized advances in bootstrap methods for long-range dependent time series data. The stationary linear long-memory process is briefly described, which is a target process for bootstrap methodologies on time-domain and frequency-domain in this review. We illustrate time-domain bootstrap under long-range dependence, moving or non-overlapping block bootstraps, and the autoregressive-sieve bootstrap. In particular, block bootstrap methodologies need an adjustment factor for the distribution estimation of the sample mean in contrast to applications to weak dependent time processes. However, the autoregressive-sieve bootstrap does not need any other modification for application to long-memory. The frequency domain bootstrap for Whittle estimation is provided using parametric spectral density estimates because there is no current nonparametric spectral density estimation method using a kernel function for the linear long-range dependent time process.

• Journal of the Korean Applied Science and Technology
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• v.16 no.3
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• pp.199-203
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• 1999

The symmetric benzoxazolo carbocyanine is of industrial importance as green-sensitizing dye in the spectral sensitization of emulsion microcrystals in positive paper and negative film-making. The stability on the solvents of benzoxazolo carbocyanine dye was measured by UV-Vis spectrophotometer, and then all of solvents were stabilized sensitizer. The maximum absorption peak range in methanol, acetonitrile, acetone, DMF, dichloromethane, chloroform solvents was $501nm{\sim}511nm$. But it was identified that only methanol can be used to photographic emulsion. The photographic characteristics have contrast of 2.8, speed of 50-55$(lux{\cdot}sec)^{-1}$, fog of 0.07-0.08, respectively.

• Publications of The Korean Astronomical Society
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• v.39 no.2
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• pp.27-38
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• 2024

Line observations of young stellar objects (YSOs) at (sub)millimeter wavelengths provide essential information of gas kinematics in star and planet forming environments. For Class 0 and I YSOs, identification of Keplerian rotation is of particular interest, because it reveals presence of rotationally-supported disks that are still being embedded in infalling envelopes and enables us to dynamically measure the protostellar mass. We have developed a python library SLAM (Spectral Line Analysis/Modeling) with a primary focus on analyses of emission line data at (sub)millimeter wavelengths. Here, we present an overview of the pvanalysis tool from SLAM, which is designed to identify Keplerian rotation of a disk and measure the dynamical mass of a central object using a position-velocity (PV) diagram of emission line data. The advantage of this tool is that it analyzes observational features of given data and thus requires few computational time and parameter assumptions, in contrast to detailed radiative transfer modelings. In this article, we introduce the basic concept and usage of this tool, present an application to observational data, and discuss remaining caveats.