• Title/Summary/Keyword: 평균 밝기

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Correction of Lunar Irradiation Effect and Change Detection Using Suomi-NPP Data (VIIRS DNB 영상의 달빛 영향 보정 및 변화 탐지)

  • Lee, Boram;Lee, Yoon-Kyung;Kim, Donghan;Kim, Sang-Wan
    • Korean Journal of Remote Sensing
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    • v.35 no.2
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    • pp.265-278
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    • 2019
  • Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) data help to enable rapid emergency responses through detection of the artificial and natural disasters occurring at night. The DNB data without correction of lunar irradiance effect distributed by Korea Ocean Science Center (KOSC) has advantage for rapid change detection because of direct receiving. In this study, radiance differences according to the phase of the moon was analyzed for urban and mountain areas in Korean Peninsula using the DNB data directly receiving to KOSC. Lunar irradiance correction algorithm was proposed for the change detection. Relative correction was performed by regression analysis between the selected pixels considering the land cover classification in the reference DNB image during the new moon and the input DNB image. As a result of daily difference image analysis, the brightness value change in urban area and mountain area was ${\pm}30$ radiance and below ${\pm}1$ radiance respectively. The object based change detection was performed after the extraction of the main object of interest based on the average image of time series data in order to reduce the matching and geometric error between DNB images. The changes in brightness occurring in mountainous areas were effectively detected after the calibration of lunar irradiance effect, and it showed that the developed technology could be used for real time change detection.

Distribution of Hydrometeors and Surface Emissivity Derived from Microwave Satellite Observations and Model Reanalyses (위성관측(MSU)과 모델 재분석 자료에서 조사된 대기물현상과 표면 방출율의 분포)

  • Kim, Tae-Yean;Yoo, Jung-Moon
    • Journal of the Korean earth science society
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    • v.23 no.7
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    • pp.552-564
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    • 2002
  • The data of satellite-observed Microwave Sounding Unit (MSU) channel 1 (Ch1) brightness temperature and General Circulation Model (GCM) reanalyses over the globe have been used to investigate low tropospheric hydrometeors and microwave surface emissivity during the period from January 1981 to December 1993. The average of GCM Ch1 temperature has been reconstructed from three kinds of reanalyses, based on the MSU weighting function. Since the GCM temperature mainly corresponds to the thermal state of the lower troposphere without the difference in the emissivity between ocean and land, it is higher in summer than in other seasons over the regions. The MSU temperature over the ocean shows its maximum at the ITCZ and the SPCZ due to hydrometeors. Over high latitude ocean, the temperature is enhanced because of sea ice emissivity, while it is reduced over the land. The seasonal displacement of the ITCZ and the SPCZ systematically appeared in the difference of Ch1 temperature between the GCM and the MSU. The difference values decrease in the regions of the ITCZ, the SPCZ, and the sea ice because of the increase of the MSU temperature. According to the local minima of the values, the ITCZ moves norhward to 9 N in fall, and the SPCZ moves southward to 12 S in boreal fall and winter. The sea ice in the northern hemisphere is extended southward to 53 N in winter, while the ice in the southern hemisphere, northward to 58 S in boreal summer. We also have discussed the separated contribution from hydrometeors and surface emissivity to the MSU Ch1 temperature, utilizing radiative transfer theory. The increase of 4-6K in the temperature over the ITCZ is inferred to result from hydrometeors of 1-1.5mm/day, and furthermore the increase of 10-30K over the high latitude ocean, ice emissivity of 0.6-0.9.

Automatic prostate segmentation method on dynamic MR images using non-rigid registration and subtraction method (동작 MR 영상에서 비강체 정합과 감산 기법을 이용한 자동 전립선 분할 기법)

  • Lee, Jeong-Jin;Lee, Ho;Kim, Jeong-Kon;Lee, Chang-Kyung;Shin, Yeong-Gil;Lee, Yoon-Chul;Lee, Min-Sun
    • Journal of Korea Multimedia Society
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    • v.14 no.3
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    • pp.348-355
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    • 2011
  • In this paper, we propose an automatic prostate segmentation method from dynamic magnetic resonance (MR) images. Our method detects contrast-enhanced images among the dynamic MR images using an average intensity analysis. Then, the candidate regions of prostate are detected by the B-spline non-rigid registration and subtraction between the pre-contrast and contrast-enhanced MR images. Finally, the prostate is segmented by performing a dilation operation outward, and sequential shape propagation inward. Our method was validated by ten data sets and the results were compared with the manually segmented results. The average volumetric overlap error was 6.8%, and average absolute volumetric measurement error was 2.5%. Our method could be used for the computer-aided prostate diagnosis, which requires an accurate prostate segmentation.

Study of the Haar Wavelet Feature Detector for Image Retrieval (이미지 검색을 위한 Haar 웨이블릿 특징 검출자에 대한 연구)

  • Peng, Shao-Hu;Kim, Hyun-Soo;Muzzammil, Khairul;Kim, Deok-Hwan
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.47 no.1
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    • pp.160-170
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    • 2010
  • This paper proposes a Haar Wavelet Feature Detector (HWFD) based on the Haar wavelet transform and average box filter. By decomposing the original image using the Haar wavelet transform, the proposed detector obtains the variance information of the image, making it possible to extract more distinctive features from the original image. For detection of interest points that represent the regions whose variance is the highest among their neighbor regions, we apply the average box filter to evaluate the local variance information and use the integral image technique for fast computation. Due to utilization of the Haar wavelet transform and the average box filter, the proposed detector is robust to illumination change, scale change, and rotation of the image. Experimental results show that even though the proposed method detects fewer interest points, it achieves higher repeatability, higher efficiency and higher matching accuracy compared with the DoG detector and Harris corner detector.

An Efficient Image Registration Based on Multidimensional Intensity Fluctuation (다차원 명암도 증감 기반 효율적인 영상정합)

  • Cho, Yong-Hyun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.22 no.3
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    • pp.287-293
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    • 2012
  • This paper presents an efficient image registration method by measuring the similarity, which is based on multi-dimensional intensity fluctuation. Multi-dimensional intensity which considers 4 directions of the image, is applied to reflect more properties in similarity decision. And an intensity fluctuation is also applied to measure comprehensively the similarity by considering a change in brightness between the adjacent pixels of image. The normalized cross-correlation(NCC) is calculated by considering an intensity fluctuation to each of 4 directions. The 5 correlation coefficients based on the NCC have been used to measure the registration, which are total NCC, the arithmetical mean and a simple product on the correlation coefficient of each direction and on the normalized correlation coefficient by the maximum NCC, respectively. The proposed method has been applied to the problem for registrating the 22 face images of 243*243 pixels and the 9 person images of 500*500 pixels, respectively. The experimental results show that the proposed method has a superior registration performance that appears the image properties well. Especially, the arithmetical mean on the correlation coefficient of each direction is the best registration measure.

Application of Computer-Aided Diagnosis a using Texture Feature Analysis Algorithm in Breast US images (유방 초음파영상에서 질감특성분석 알고리즘을 이용한 컴퓨터보조진단의 적용)

  • Lee, Jin-Soo;Kim, Changsoo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.1
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    • pp.507-515
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    • 2015
  • This paper suggests 6 cases of TFA parameters algorithm(Mean, VA, RS, SKEW, UN, EN) to search for the detection of recognition rates regarding breast disease using CAD on ultrasound images. Of the patients who visited a university hospital in Busan city from August 2013 to January 2014, 90 cases of breast ultrasound images based on the findings in breast US and pathology were selected. $50{\times}50$ pixel size ROI was selected from the breast US images. After pre-processing histogram equalization of the acquired test images(negative, benign, malignancy), we calculated results of TFA algorithm using MATLAB. As a result, in the TFA parameters suggested, the disease recognition rates for negative and malignancy was as high as 100%, and negative and benign was approximately 83~96% for the Mean, SKEW, UN, and EN. Therefore, there is the possibility of auto diagnosis as a pre-processing step for a screening test on breast disease. A additional study of the suggested algorithm and the responsibility and reproducibility for various clinical cases will determine the practical CAD and it might be possible to apply this technique to range of ultrasound images.

Chromatic adaptation model for the variations of the luminance of the same chromaticity illuminants (동일 색도 광원의 휘도 변화에 따른 색 순응 모델)

  • Kim Eun-Su;Jang Soo-Wook;Lee Sung-Hak;Sohng Kyu-lk
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.4 s.304
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    • pp.31-38
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    • 2005
  • In this paper, we propose the chromatic adaptation models (CAM) for the variations of the luminance levels. A chromatic adaptation model, CAM$\Delta$Y , is proposed according to the change of luminance level under the same illuminants. The proposed model is obtained by the transform the test colors of the high luminance into the corresponding colors of the low luminance. In the proposed model, the optimal coefficients are obtained from the corresponding colors data of the Breneman's experiments. In the experimental results, we confined that the chromaticity errors, $\Delta$u'v', between the predicted colors by the proposed model and the corresponding colors of the Breneman's experiments are 0.004 in u'v' chromaticity coordinates. The prediction performance of the proposed model is excellent because this error is the threshold value that two adjacent color patches can be distinguished. Additionally, we also propose equal-whiteness CCT curves (EWCs) by CAM$\Delta$Y according to the luminance levels of the surround viewing conditions. And the proposed EWCs can be used as the theoretical standard which determines the reference white of the color display devices.

Edge-Enhanced Error Diffusion Halftoning using Local mean and Spatial Activity (국부 평균과 공간 활성도를 이용한 에지 강조 오차확산법)

  • Kwak Nae-Joung;Kwon Dong-Jin;Kim Young-Gil;Ahn Jae-Hyeong
    • The KIPS Transactions:PartB
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    • v.13B no.2 s.105
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    • pp.77-82
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    • 2006
  • Digital halftoning is the technique to obtain a bilevel-toned image from continuous-toned image. Among halftoning methods, the error diffusion method gives better subjective quality than other halftoning ones. But it also makes edges of objects blurred. To overcome the defect, we proposes the modified error diffusion to enhance the edges using the property that human vision perceives the local average luminance and doesn't perceive a little variation of the spatial variation. The proposed method computes a spatialactivity, which is the difference between a pixel luminance and the average of its $3{\times}3$ neighborhood pixels' Iuminance weighted according to the spatial positioning. The system also usesof edge enhancement (IEE), which is computed from the normalized spatial activitymultiplied by the average luminance. The IEE is added to the quantizer's input pixel and feeds into the halftoning quantizer. The quantizer produces the halftone image having the enhanced edge. The computer experimental results show that the proposed method produces clearer bilevel-toned images than conventional methodsand the edge of objects is preserved well. Also the performance of the preposed method is improved, compared with that of the conventional method by measuring the edge correlation and the local average accordance at some ranges of viewing distance.

Frequency Mudularized Deinterlacing Using Neural Network (신경회로망을 이용한 주파수 모듈화된 deinterlacing)

  • 우동헌;엄일규;김유신
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.28 no.12C
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    • pp.1250-1257
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    • 2003
  • Generally images are classified into two regions: edge and flat region. While low frequency components are popular in the flat region, high frequency components are quite important in the edge region. Therefore, deinterlacing algorithm that considers the characteristic of each region can be more efficient. In this paper, an image is divided into edge region and flat region by the local variance. And then, for each region, frequency modularized neural network is assigned. Using this structure, each modularized neural network can learn only its region intensively and avoid the complexity of learning caused by the data of different region. Using the local AC data for the input of neural network can prevent the degradation of the performance of teaming due to the average intensity values of image that disturbs the effective learning. The proposed method shows the improved performance compared with previous algorithms in the simulation.

Prostate Object Extraction in Ultrasound Volume Using Wavelet Transform (초음파 볼륨에서 웨이브렛 변환을 이용한 전립선 객체 추출)

  • Oh Jong-Hwan;Kim Sang-Hyun;Kim Nam-Chul
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.43 no.3 s.309
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    • pp.67-77
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    • 2006
  • This thesis proposes an effi챠ent method for extracting a prostate volume from 3D ultrasound image by using wavelet transform and SVM classification. In the proposed method, a modulus image for each 2D slice is generated by averaging detail images of horizontal and vertical orientations at several scales, which has the sharpest local maxima and the lowest noise power compared to those of all single scales. Prostate contour vertices are determined accurately using a SVM classifier, where feature vectors are composed of intensity and texture moments investigated along radial lines. Experimental results show that the proposed method yields absolute mean distance of on average 1.89 pixels when the contours obtained manually by an expert are used as reference data.