• 제목/요약/키워드: visible bands

검색결과 168건 처리시간 0.03초

영역별 대역간 양방향 예측과 확장된 SPIHT를 이용한 다분광 화상데이터의 압축 (Multispectral Image Compression Using Classified Interband Bidirectional Prediction and Extended SPHT)

  • 김승진;반성원;김병주;박경남;김영춘;이건일
    • 대한전자공학회논문지SP
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    • 제39권5호
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    • pp.486-493
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    • 2002
  • 본 논문에서는 웨이블릿 영역에서 각 부밴드에 대한 영역별 대역간 양방향 예측과 확장된 SPIHT (set partition in hierarchical trees)를 이용한 효율적인 인공위성 다분광 화상데이터의 압축 방법을 제안하였다. 이 방법에서는 가시광선 영역과 적외선 영역에서 다른 대역과 분광적 상관성이 큰 대역을 기준대역 (feature band)으로 각각 결정하고, 이 대역들에 대해 웨이블릿 변환 (wavelet transform, WT)을 행한 후 SPIHT를 행하여 부호화함으로써 대역내 (intraband) 중복성을 제거한다. 기준대역과 대역간 상관성이 큰 예측대역 (prediction band)들에 대해서는 웨이블릿 변환을 행한 후, 각 대역의 기저밴드의 대역별 특성을 이용하여 영역분류를 하고, 각 부밴드에 대한 영역별 대역간 양방향 예측 (classified interband bidirec- tional prediction)을 행함으로써 대역간 (interband) 중복성을 제거하여 압축 효율을 향상시킨다. 또한 확장된 SPIHT의 부호화 효율을 높이기 위해 예측오차의 최대값에 따라 재배열된 대역들에 대해 확장된 SPIHT를 행하여 예측오차를 부호화함으로써, 예측에 따른 오차를 보상하여 화질을 향상시킨다. 실제 다분광 화상데이터에 대한 모의 실험을 통하여 제안한 방법의 부호화 효율이 기존의 방법에 비하여 우수함을 확인하였다.

The Modification of Exocyclic Ketone on Methyl(Pyro) pheophorbide-a and Influence with Visible Spectra

  • Wang, Jin-Jun;Han, Guang-Fan;Shim, Young-Key
    • Journal of Photoscience
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    • 제8권1호
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    • pp.23-25
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    • 2001
  • The methyl pheophorbide-a (MP-a) and methyl pyropheophorbide-a (MPP-a) were modified by reaction of exocyclic ketone in E-ring with nucleophilic reagent and several chlorin derivatives were synthesized. The change of the structure in E-ring served an expanding conjugation region and introduction of electron-withdrawing group, which strongly influenced the visible spectra. The Qy bands of synthesized compounds were affected by the substituents on the Qy axis(N$\sub$21/-N$\sub$23/).

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RFID-automated Smart Air-cargo Movement System

  • 소신;전광현;장경희
    • 한국통신학회논문지
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    • 제36권12B호
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    • pp.1686-1697
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    • 2011
  • This paper aims to build up a RFID-automated cargo movement system in an air-cargo warehouse. In our research, we do the spectrum measurements compliant with the RFID frequency bands to observe the interferences from legacy systems in the air-cargo warehouse. To overcome the dense-reader mode (DRM) problem, we apply three novel approaches, which are the periodic transmit of a reader, the Visible RFID reader & tag, and the sensor-based RFID system. Moreover, for the tag collision issue, we implement the Adaptive Adjustable Framed Q(AAFQ) algorithm, and the demonstration on RFID tag anti-collision algorithms show that the AAFQ algorithm has highly desirable tag anti-collision performance compared to any other commercially available solutions.

소형 다중분광 항공촬영 시스템(PKNU 3호) 개발에 관한 연구 (Research for development of small format multi -spectral aerial photographing systems (PKNU 3))

  • 이은경;최철웅;서영찬;조남춘
    • 한국측량학회:학술대회논문집
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    • 한국측량학회 2004년도 추계학술발표회 논문집
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    • pp.143-152
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    • 2004
  • Researchers seeking geological and environmental information, depend on remote sensing and aerial photographic datum from various commercial satellites and aircraft. However, adverse weather conditions as well as equipment expense limit the ability to collect data anywhere and anytime. To allow for better flexibility in geological and environmental data collection, we have developed a compact, multi-spectral automatic Aerial Photographic system (PKNU2). This system's Multi-spectral camera can record visible (RGB) and infrared (NIR) band (3032*2008 Pixels) images Visible and infrared band images were obtained from each camera respectively and produced color-infrared composite images to be analyzed for the purpose of the environmental monitoring. However this did not provide quality data. Furthermore, it has the disadvantage of having the stereoscopic overlap area being 60% unsatisfied due to the 12 seconds of storage time of each data The PKNU2 system in contrast, photographed photos of great capacity Thus, with such results, we have been proceeding to develop the advanced PKNU2 (PKNU3) system that consists of a color-infrared spectral camera that can photograph in the visible and near-infrared bands simultaneously using a single sensor, a thermal infrared camera, two 40G computers to store images, and an MPEG board that can compress and transfer data to the computer in real time as well as be able to be mounted onto a helicopter platform.

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Electrochemical and Spectroelectrochemical Behaviors of Vitamin K1/Lipid Modified Electrodes and the Formation of Radical Anion in Aqueous Media

  • Yang, Jee-Eun;Yoon, Jang-Hee;Won, Mi-Sook;Shim, Yoon-Bo
    • Bulletin of the Korean Chemical Society
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    • 제31권11호
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    • pp.3133-3138
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    • 2010
  • The electrochemical properties of the liposoluble vitamin $K_1$ adsorbed on bare and lipid coated glassy carbon electrodes (GCEs) were studied in unbuffered and well buffered aqueous media. The reduction products of vitamin $K_1$ were characterized by employing cyclic voltammetry and the in situ UV-visible spectroelectrochemical technique. The radical species of vitamin $K_1$ cannot be observed at the bare GCEs in well buffered media. The formation of the anion radical of vitamin $K_1$ was observed in unbuffered solutions above pH 5.9 or at the lipid coated GCE in a well-buffered solution. UV-visible absorption bands of neutral vitamin $K_1$ were observed at 260 nm and 330 nm, and a band corresponding to the anion radical species was observed at 450 nm. The derivative cyclic voltabsorptometric (DCVA) curves obtained for electrochemical reduction of vitamin $K_1$ confirmed the presence of both neutral and anion radical species. The anion radical of vitamin $K_1$ formed at the hydrophobic conditions with phosphatidylcholine (PC) lipid coated electrode was stable enough to be observed in the spectroelectrochemical experiments.

오디오 스펙트럼을 이용한 LED 감성 조명 알고리즘과 응용 (LED Emotional Lighting Algorithm and Application using Audio Spectrum)

  • 장영범;석상철
    • 한국통신학회논문지
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    • 제36권10B호
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    • pp.1252-1257
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    • 2011
  • 이 논문에서는 오디오 신호의 스펙트럼 가시광선 스펙트럼으로 매핑하는 감성 조명 방식을 제안한다. 인간의 청각이 인지하는 오디오 스펙트럼의 전 대역을 시각이 인지하는 가시광 스펙트럼의 전 대역으로 매핑하는 조명 알고리즘을 제안하며 특히 기본적인 선행 매핑 방식과 특정 주파수 대역을 가조하는 비선형 스펙트럼 매핑 방식에 대하여 논한다. 알고리즘의 효과를 실험하기 위하여 DSP 보드로 구현함으로써 제안된 조명 방식의 응용 가능성을 보였다. 따라서 제안된 조명 방식은 스탠드 LED 조명, 화병 LED 조명, 분수용 LED 조명, 건축물용 LED 조명, 노래방용 LED 조명, 청각 장애인용 LED 음악조명 등의 분야에 응용될 수 있을 것이다.

Spectroscopic Properties and Ligand Field Analysis of cis-Dinitrato(1,4,8,11-tetraazacyclotetradecane)chromium(III) Nitrate

  • 최종하
    • Bulletin of the Korean Chemical Society
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    • 제18권8호
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    • pp.819-823
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    • 1997
  • The luminescence and photoexcitation spectra of cis-[Cr(cyclam)(NO3)2]NO3·½ H2O (cyclam=1,4,8,11-tetraazacyclotetradecane) taken at 77 K are reported. The infrared and visible spectra at room-temperature are also measured. The vibrational intervals of the electronic ground state are extracted from the far-infrared and emission spectra. The ten electronic bands due to spin-allowed and spin-forbidden transitions are assigned. With observed transitions, a ligand field analysis has been performed to determine the bonding property of nitrate group in the chromium(Ⅲ) complex. According to the results, it is found that nitrate ligand has weak σ- and π-donor properties toward chromium(Ⅲ).

Hierarchical Clustering Approach of Multisensor Data Fusion: Application of SAR and SPOT-7 Data on Korean Peninsula

  • Lee, Sang-Hoon;Hong, Hyun-Gi
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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    • pp.65-65
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    • 2002
  • In remote sensing, images are acquired over the same area by sensors of different spectral ranges (from the visible to the microwave) and/or with different number, position, and width of spectral bands. These images are generally partially redundant, as they represent the same scene, and partially complementary. For many applications of image classification, the information provided by a single sensor is often incomplete or imprecise resulting in misclassification. Fusion with redundant data can draw more consistent inferences for the interpretation of the scene, and can then improve classification accuracy. The common approach to the classification of multisensor data as a data fusion scheme at pixel level is to concatenate the data into one vector as if they were measurements from a single sensor. The multiband data acquired by a single multispectral sensor or by two or more different sensors are not completely independent, and a certain degree of informative overlap may exist between the observation spaces of the different bands. This dependence may make the data less informative and should be properly modeled in the analysis so that its effect can be eliminated. For modeling and eliminating the effect of such dependence, this study employs a strategy using self and conditional information variation measures. The self information variation reflects the self certainty of the individual bands, while the conditional information variation reflects the degree of dependence of the different bands. One data set might be very less reliable than others in the analysis and even exacerbate the classification results. The unreliable data set should be excluded in the analysis. To account for this, the self information variation is utilized to measure the degrees of reliability. The team of positively dependent bands can gather more information jointly than the team of independent ones. But, when bands are negatively dependent, the combined analysis of these bands may give worse information. Using the conditional information variation measure, the multiband data are split into two or more subsets according the dependence between the bands. Each subsets are classified separately, and a data fusion scheme at decision level is applied to integrate the individual classification results. In this study. a two-level algorithm using hierarchical clustering procedure is used for unsupervised image classification. Hierarchical clustering algorithm is based on similarity measures between all pairs of candidates being considered for merging. In the first level, the image is partitioned as any number of regions which are sets of spatially contiguous pixels so that no union of adjacent regions is statistically uniform. The regions resulted from the low level are clustered into a parsimonious number of groups according to their statistical characteristics. The algorithm has been applied to satellite multispectral data and airbone SAR data.

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가시 밴드와 근적외 밴드를 이용한 해무 탐지 알고리즘 (Sea Fog Detection Algorithm Using Visible and Near Infrared Bands)

  • 이경훈;권병혁;윤홍주
    • 한국전자통신학회논문지
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    • 제13권3호
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    • pp.669-676
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    • 2018
  • GOCI(: Geostationary Ocean Color Imager)는 8개 밴드의 레일리 보정 반사도를 이용하여 수평 $500m{\times}500m$의 높은 공간 해상도로 해무를 탐지한다. 가시광선과 근적외선은 지표면의 특성을 강하게 반영하여 구름과 안개 판별에 오차를 유발한다. Band7 반사도의 임계값을 설정하여 육지로 유입되는 해무를 탐지할 수 있었다. Band4 반사도가 Band8보다 크게 나타나는 영역이 구름으로 판별되는 경우는 주변 영역과 평균 반사도의 비교를 통해 해무로 탐지되는 오류를 보정하였다. 개선된 알고리즘은 천리안위성(COMS: Communication, Ocean, Meteorological Satellite)의 안개 영상 및 기상청 시정계 자료와 비교하여 검증되었다.

Relating Hyperspectral Image Bands and Vegetation Indices to Corn and Soybean Yield

  • Jang Gab-Sue;Sudduth Kenneth A.;Hong Suk-Young;Kitchen Newell R.;Palm Harlan L.
    • 대한원격탐사학회지
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    • 제22권3호
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    • pp.183-197
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    • 2006
  • Combinations of visible and near-infrared (NIR) bands in an image are widely used for estimating vegetation vigor and productivity. Using this approach to understand within-field grain crop variability could allow pre-harvest estimates of yield, and might enable mapping of yield variations without use of a combine yield monitor. The objective of this study was to estimate within-field variations in crop yield using vegetation indices derived from hyperspectral images. Hyperspectral images were acquired using an aerial sensor on multiple dates during the 2003 and 2004 cropping seasons for corn and soybean fields in central Missouri. Vegetation indices, including intensity normalized red (NR), intensity normalized green (NG), normalized difference vegetation index (NDVI), green NDVI (gNDVI), and soil-adjusted vegetation index (SAVI), were derived from the images using wavelengths from 440 nm to 850 nm, with bands selected using an iterative procedure. Accuracy of yield estimation models based on these vegetation indices was assessed by comparison with combine yield monitor data. In 2003, late-season NG provided the best estimation of both corn $(r^2\;=\;0.632)$ and soybean $(r^2\;=\;0.467)$ yields. Stepwise multiple linear regression using multiple hyperspectral bands was also used to estimate yield, and explained similar amounts of yield variation. Corn yield variability was better modeled than was soybean yield variability. Remote sensing was better able to estimate yields in the 2003 season when crop growth was limited by water availability, especially on drought-prone portions of the fields. In 2004, when timely rains during the growing season provided adequate moisture across entire fields and yield variability was less, remote sensing estimates of yield were much poorer $(r^2<0.3)$.