• Title/Summary/Keyword: Pure Pixel

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Extraction of the aquaculture farms information from the Landsat- TM imagery of the Younggwang coastal area

  • Shanmugam, P.;Ahn, Yu-Hwan;Yoo, Hong-Ryong
    • 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.

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Accuracy Evaluation of Supervised Classification about IKONOS Imagery using Mixed Pixels (혼합화소를 이용한 IKONOS 영상의 감독분류정확도 평가)

  • Lee, Jong-Sin;Kim, Min-Gyu;Park, Joon-Kyu
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.13 no.6
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    • pp.2751-2756
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    • 2012
  • Selection of training set influences the classification accuracy in supervised classification using satellite imagery. Generally, if pure pixels which character of training set is clear were selected, whole accuracy is high while if mixed pixels were selected, accuracy is decreased because of low-resolution imagery or unclear distinguishment. However, it is too difficult to choose the pure pixels as training set actually. Accordingly, this study should be suggested the suitable classification method in case of mixed pixels choice. To achieve this, a few pure pixels were chosen as training set and classification accuracy was calculated which was compared with classification result using an equal number of mixed pixels. As a result, accuracy of SVM was the highest among the classification method using mixed pixels and it was a relatively small difference with the result of classification using pure pixels. Therefore, imagery classification using SVM is most suitable in the mixed area of construction and green because it is high possibility to choose mixed pixels as training set.

A Charge-Pump Passive-Matrix Pixel Driver for Organic Light Emitting Diodes

  • Seo, Jong-Wook;Kim, Han-Byul;Kim, Bong-Ok;Kim, Young-Kwan
    • 한국정보디스플레이학회:학술대회논문집
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    • 2002.08a
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    • pp.108-112
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    • 2002
  • A new pixel driving method for organic light-emitting diode (OLED) flat-panel display (FPD) is proposed. The new charge-pump passive-matrix pixel driver consists only of a storage capacitance and a rectifying diode, and no thin-film transistor (TFT) is needed. The new driver not only supplies a constant current to the OLED throughout the whole period of panel scanning like an active-matrix driver, but also provides a highly linear gray-scale control through a pure digital manner.

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Decomposition of category mixture in a pixel and its application for supervised image classification

  • Matsumoto, Masao;Arai, Kohei;Ishimatsu, Takakazu
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10b
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    • pp.514-519
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    • 1992
  • To make an accurate retrieval of the proportion of each category among mixed pixels (Mixel's) of a remotely sensed imagery, a maximum likelihood estimation method of category proportion is proposed. In this method, the observed multispectral vector is considered as probability variables along with the approximation that the supervised data of each category can be characterized by normal distribution. The results show that this method can retrieve accurate proportion of each category among Mixel's. And a index that can estimate the degree of error in each category is proposed. AS one of the application of the proportion estimation, a method for image classification based on category proportion estimation is proposed. In this method all pixel in a remotely sensed imagery are assumed to be Mixel's, and are classified to most dominant category. Among the Mixel's, there exists unconfidential pixels which should be categorized as unclassified pixels. In order to discriminate them, two types of criteria, Chi square and AIC, are proposed for fitness test on pure pixel hypothesis. Experimental result with a simulated dataset show an usefulness of proposed classification criterion compared to the conventional maximum likelihood criterion and applicability of the fitness tests based on Chi square and AIC,

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Fully Cu-based Gate and Source/Drain Interconnections for Ultrahigh-Definition LCDs

  • Kugimiya, Toshihiro;Goto, Hiroshi;Hino, Aya;Nakai, Junichi;Yoneda, Yoichiro;Kusumoto, Eisuke
    • 한국정보디스플레이학회:학술대회논문집
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    • 2009.10a
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    • pp.1193-1196
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    • 2009
  • Low resistivity interconnection and high-mobility channel are required to realize ultrahigh-definition LCDs such as 4k ${\times}$ 2k TVs. We evaluated fully Cu-based gate and Source/Drain interconnections, consisting of stacked pure-Cu/Cu-Mn layers for TFT-LCDs, and found the underlying Cu-Mn alloy film has superior adhesion to glass substrates and CVD-SiOx films. It was also confirmed that wet etching of the Cu/Cu-Mn films without residues and low contact resistance with both channel IGZO and pixel ITO films can be obtained. It is thus considered that the stacked Cu/Cu-Mn structure is one of candidates to replacing conventionally pure-Cu/refractory metal.

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Support Vector Machine Classification Using Training Sets of Small Mixed Pixels: An Appropriateness Assessment of IKONOS Imagery

  • Yu, Byeong-Hyeok;Chi, Kwang-Hoon
    • Korean Journal of Remote Sensing
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    • v.24 no.5
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    • pp.507-515
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    • 2008
  • Many studies have generally used a large number of pure pixels as an approach to training set design. The training set are used, however, varies between classifiers. In the recent research, it was reported that small mixed pixels between classes are actually more useful than larger pure pixels of each class in Support Vector Machine (SVM) classification. We evaluated a usability of small mixed pixels as a training set for the classification of high-resolution satellite imagery. We presented an advanced approach to obtain a mixed pixel readily, and evaluated the appropriateness with the land cover classification from IKONOS satellite imagery. The results showed that the accuracy of the classification based on small mixed pixels is nearly identical to the accuracy of the classification based on large pure pixels. However, it also showed a limitation that small mixed pixels used may provide insufficient information to separate the classes. Small mixed pixels of the class border region provide cost-effective training sets, but its use with other pixels must be considered in use of high-resolution satellite imagery or relatively complex land cover situations.

Quantitative Visualization of Oxygen Transfer in Micro-channel using Micro-LIF Technique (마이크로 레이저 형광 여기법을 이용한 미세채널 내부에서의 산소 확산에 대한 정량적 가시화)

  • Chen, Juan;Kim, Hyun-Dong;Kim, Kyung-Chun
    • Journal of the Korean Society of Visualization
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    • v.10 no.1
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    • pp.34-39
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    • 2012
  • In the present study, oxygen transfer process across gas-liquid interface in a Y-shape micro-channel is quantitatively visualized using the micro laser induced fluorescence (${\mu}$-LIF) technique. Diffusion coefficient of Oxygen ($D_L$) is estimated based on the experimental results and compared to its theoretical value. Tris ruthenium (II) chloride hexahydrate was used as the oxygen quenchable fluorescent dye. A light-emitting diode (LED) with wavelength of 450 nm was used as the light source and phosphorescence images of fluorescent dye were captured by a CMOS high speed camera installed on the microscope system. Water having dissolved oxygen (DO) value of 0% and pure oxygen gas were injected into the Y-shaped microchannel by using a double loading syringe pump. In-situ pixel-by-pixel calibration was carried out to obtain Stern-Volmer plots over whole flow field. Instantaneous DO concentration fields were successfully mapped according to Stern-Volmer plots and DL was calculated as $2.0675{\times}10^{-9}\;m^2/s$.

Codebook-Based Foreground Extraction Algorithm with Continuous Learning of Background (연속적인 배경 모델 학습을 이용한 코드북 기반의 전경 추출 알고리즘)

  • Jung, Jae-Young
    • Journal of Digital Contents Society
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    • v.15 no.4
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    • pp.449-455
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    • 2014
  • Detection of moving objects is a fundamental task in most of the computer vision applications, such as video surveillance, activity recognition and human motion analysis. This is a difficult task due to many challenges in realistic scenarios which include irregular motion in background, illumination changes, objects cast shadows, changes in scene geometry and noise, etc. In this paper, we propose an foreground extraction algorithm based on codebook, a database of information about background pixel obtained from input image sequence. Initially, we suppose a first frame as a background image and calculate difference between next input image and it to detect moving objects. The resulting difference image may contain noises as well as pure moving objects. Second, we investigate a codebook with color and brightness of a foreground pixel in the difference image. If it is matched, it is decided as a fault detected pixel and deleted from foreground. Finally, a background image is updated to process next input frame iteratively. Some pixels are estimated by input image if they are detected as background pixels. The others are duplicated from the previous background image. We apply out algorithm to PETS2009 data and compare the results with those of GMM and standard codebook algorithms.

A Modified Iterative N-FINDR Algorithm for Fully Automatic Extraction of Endmembers from Hyperspectral Imagery (초분광 영상의 endmember 자동 추출을 위한 수정된 Iterative N-FINDR 기법 개발)

  • Kim, Kwang-Eun
    • Korean Journal of Remote Sensing
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    • v.27 no.5
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    • pp.565-572
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    • 2011
  • A modified iterative N-FINDR algorithm is developed for fully automatic extraction of endmembers from hyperspectral image data. This algorithm exploits the advantages of iterative NFINDR technique and Iterative Error analysis technique. The experiments using a simulated hyperspectral image data shows that the optimum number of endmembers can be automatically decided. The extracted endmembers and finally generated abundance fraction maps show the potentialities of the proposed algorithm. More studies are needed for verification of the applicability of the algorithm to the real hyperspectral image data where the absence of pure pixels is common.

Evaluating Apparatus for the ICA-Aided Mixel Analysis of Periodical Hyperspectral Images

  • Shimozato, Masao;Kosaka, Naoko;Uto, Kuniaki;Kosugi, Yukio
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.411-413
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    • 2003
  • In the images obtained from high altitude, several materials are mixed in one pixel and observed as a mixel. It makes difficult to separate the value of pure materials from obtained data. As mixel analysis, various techniques using Independent Component Analysis (ICA) and wavelet analysis, etc, were proposed. In this study, we applied to the ICA technique to real data collected by hyperspectral line sensor. Real data came under the influence of several effects regarded as basin on the convolution. We show that combining the ICA method with deconvolution improve it's estimation ability.

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