• The Journal of the Acoustical Society of Korea
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• v.31 no.7
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• pp.472-479
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• 2012

This paper is aimed to design 9.2 kbps low bits late transform excitation coder that target to voice and audio signal. To set up low bit rate, we used Band-selection in frequency domain and gain-shape quantization and AbS structure. To decrease lots of calculation from ABS structure, we used each band IDFT and synthesis. And we designed non-transfer band for performance by inserting comfort noise. We propose coder that has low bit rate and similar performance comparing with original 10.4 kbps AMR-WB+ TCX mode.

• The Journal of the Acoustical Society of Korea
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• v.14 no.1E
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• pp.46-55
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• 1995

In this paper, we present a new wavelet transform-based CELP coder, called band selection wavelet transform CELP (BS-WTCELP) operated at 4.8 kbps. The proposed algorithm uses a band selection scheme of frequency bands of wavelet transform and selective vector quantization (VQ). The band selection and selective VQ structure is implemented by using a classified VQ structure. The proposed algorithm has about 0.5-1.0 dB improvement in segmental SNR compared with the conventional CELP that uses the random codebook search, while is has significantly reduced computational and storage complexity. Many experimental results have shown that the proposed algorithm is more suitable for most real-applications than the conventional CELP and wavelet transform CELP.

• Management & Information Systems Review
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• v.3
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• pp.15-45
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• 1999

Processing techniques of remote sensed image data using computer have been recognized very necessary techniques to all social fields, such as, environmental observation, land cultivation, resource investigation, military trend grasp and agricultural product estimation, etc. Especially, accurate classification and analysis to remote sensed image da are important elements that can determine reliability of remote sensed image data processing systems, and many researches have been processed to improve these accuracy of classification and analysis. Traditionally, remote sensed image data processing systems have been processed 2 or 3 selected bands in multiple bands, in this time, their selection criterions are statistical separability or wavelength properties. But, it have be bring up the necessity of bands selection method by data distribution characteristics than traditional bands selection by wavelength properties or statistical separability. Because data sensing environments change from multispectral environments to hyperspectral environments. In this paper for efficient data classification in multispectral bands environment, a band feature extraction method using the Rough sets theory is proposed. First, we make a look up table from training data, and analyze the properties of experimental multispectral image data, then select the efficient band using indiscernibility relation of Rough set theory from analysis results. Proposed method is applied to LANDSAT TM data on 2 June 1992. From this, we show clustering trends that similar to traditional band selection results by wavelength properties, from this, we verify that can use the proposed method that centered on data properties to select the efficient bands, though data sensing environment change to hyperspectral band environments.

• Korean Journal of Remote Sensing
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• v.27 no.5
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• pp.521-534
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• 2011

The high-resolution X-band SAR systems such as COSMO-SkyMED and TerraSAR-X have been launched recently. In addition KOMPSAT-5 will be launched in the early of 2012. In this study we developed the new method for persistent scatterer candidate (PSC) selection and network construction, which is more suitable for PSInSAR analysis using multi-temporal X-band SAR data. PSC selection consists in two main steps: first, selection of initial PSCs based on amplitude dispersion index, mean amplitude, mean coherence. second, selection of final PSCs based on temporal coherence directly estimated from network analysis of initial PSCs. To increase the stability of network the Multi- TIN and complex network for non-urban area were addressed as well. The proposed algorithm was applied to twenty-one TerraSAR-X SAR of New Orleans. As a result many PSs were successfully extracted even in non-urban area. This research can be used as the practical application of KOMPSAT-5 for surface displacement monitoring using X-band PSInSAR.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.2A
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• pp.139-148
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• 2011

This paper presents the minimum-cost network selection scheme which determines the transmission instance in the multi-band maritime communication system, so that the shipment-related real-time information can be transmitted within the maximum allowed period. The transmission instances and the corresponding network selection process are modeled by a Markov Decision Process (MDP), for the channel model in the 2-state Markov chain, which can be solved by stochastic dynamic programming. It derives the minimum-cost network selection rule, which can reduce the network cost significantly as compared with the straight-forward scheme with a periodic transmission.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.141-147
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• 2021

In this paper, in order to improve the utilization of hyperspectral large-capacity data feature information by reducing complex computations by dimension reduction of neural network inputs in embedded systems, the band selection algorithm is applied in each subset. Among feature extraction and feature selection techniques, the feature selection aim to improve the optimal number of bands suitable for datasets, regardless of wavelength range, and the time and performance, more than others algorithms. Through this experiment, although the time required was reduced by 1/3 to 1/9 times compared to the others band selection technique, meaningful results were improved by more than 4% in terms of performance through the K-neighbor classifier. Although it is difficult to utilize real-time hyperspectral data analysis now, it has confirmed the possibility of improvement.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.193-198
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• 2006

Among 242 Hyperion bands, there are 46 bands that contain completely no information and some other bands with various kinds of noise. It is mainly due to the atmosphenc absorption and the low signal-to-noise ratio. The visual inspection for selecting clean and stable bands is a simple practice, but is a manual, inefficient, and subjective Process. Though uncalibrated, overlapping, and all deep water absorption bands are removed, there still exist noisy bands. In this paper, we propose that the extrema ratio be measured for noise estimation and the unsupervised band selection be performed using the Expectation-Maximization algorithm. The Hyperion data were classified into 5 categories according to the image quality by visual inspection, and used as the reference data. The accuracy of the proposed method was compared with signal-to-noise ranking and entropy ranking. As a result, the proposed mettled was effective as preprocessing step for band selection.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.80.2-80.2
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• 2021

Galactic young massive clusters are the ideal laboratories to study massive stellar evolution. Unfortunately, such objects are rare. Of particular interest are so-called Red Supergiant Clusters (RSGCs) that are currently only found toward the Scutum-Crux Galactic arm. Confirming their nature as RSGC is often not straight-fortward as distinguishing RSGs from AGB stars is still difficult even with high spectral resolution spectra. Here we report that broad band colors using 2MASS JHK and GAIA G band data can be useful in reducing the AGB contamination, thus providing selection criteria that effectively reveal the known RSGCs with negligible false positives. On the other hand, we suggest that RSGC4, one of the proposed RSGC candidates, may not be a cluster of RSGs as their colors are not compatible with our selection criteria. We discuss the nature of these stars together with our IGRINS spectroscopic observations. We also employ the same selection criteria to search for RSGC candidates in other parts of the plane, resulting in no prominent candidates.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.78.3-78.3
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• 2015

About 70 high redshift quasars with $z{\geq}5$ have been discovered through combinations of standard broad-band filters to distinguish them from contaminating sources. However, among the discovered quasars so far, there is a redshift gap at $5{\leq}z{\leq}6$ due to the limitation of traditional filter sets and selection techniques. To understand the early mass growth of supermassive black holes and the final stage of the cosmic reionization, it is important to find a statistically meaningful sample of quasars with various physical properties. Here we suggest a new selection technique of high redshift quasars using medium-band filters: nine filters with bandwidths of 50nm and central wavelengths from 625 to 1025nm. Photometry with these medium-bands traces the spectral energy distribution (SED) of a source, similar to spectroscopy with R~15. We installed these filters to SED camera for QUasars in EArly uNiverse (SQUEAN) on the 2.1m telescope at McDonald Observatory, and conducted test observations of known high redshift quasars at $4.7{\leq}z{\leq}6.1$ and also dwarf stars for comparison. We found differences in SED shapes between high redshift quasars and dwarf stars, determined their locations on color-color diagrams, and demonstrated that the medium-band filters can enhance the efficiency of selecting robust quasar candidates in this redshift range. In this poster, we propose an effective selection method of high redshift quasars using these medium-band filters and discuss its effect on our high redshift quasar survey.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.5
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• pp.383-392
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• 2007

This study focuses on co-registration and band selection, which are one of the pre-processing steps to apply the change detection technique using hyperspectral images. We carried out automatic co-registration by using the SIFT algorithm which performance was already established in the computer vision fields, and selected the bands fur change detection by estimating the noise of image through the PIFs reflecting the radiometric consistency. The EM algorithm was also applied to select the band objectively. Hyperion images were used for the proposed techniques, and non-calibrated bands and striping noises contained in Hyperion image were removed. Throughout the results, we could develop the reliable co-registration procedure which coincided with accuracy within 0.2 pixels (RMSE) for change detection, and verified that band selection depending on the visual inspection could be objective by extracting the PIFs.