• Title/Summary/Keyword: Single Image

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3D BUILDING INFORMATION EXTRACTION FROM A SINGLE QUICKBIRD IMAGE

  • Kim, Hye-Jin;Han, Dong-Yeob;Kim, Yong-Il
    • Proceedings of the KSRS Conference
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    • v.1
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    • pp.409-412
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    • 2006
  • Today's commercial high resolution satellite imagery such as IKONOS and QuickBird, offers the potential to extract useful spatial information for geographical database construction and GIS applications. Recognizing this potential use of high resolution satellite imagery, KARI is performing a project for developing Korea multipurpose satellite 3(KOMPSAT-3). Therefore, it is necessary to develop techniques for various GIS applications of KOMPSAT-3, using similar high resolution satellite imagery. As fundamental studies for this purpose, we focused on the extraction of 3D spatial information and the update of existing GIS data from QuickBird imagery. This paper examines the scheme for rectification of high resolution image, and suggests the convenient semi-automatic algorithm for extraction of 3D building information from a single image. The algorithm is based on triangular vector structure that consists of a building bottom point, its corresponding roof point and a shadow end point. The proposed method could increase the number of measurable building, and enhance the digitizing accuracy and the computation efficiency.

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A Study on the Panoramic Image Generation in the Sea Environment (해상 환경에서의 파노라믹 영상 생성 기법에 관한 연구)

  • 김효성;김길중
    • Journal of the Institute of Convergence Signal Processing
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    • v.3 no.3
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    • pp.41-46
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    • 2002
  • We generally used electric optical sensors in order to detect and identify sea objects efficiently. However due to the limitation of view-angle, the region acquired from the sense is restricted. So it is necessary to generate panoramic image from sea images acquired from pan-tilt camera. Previous mosaicing method is not able to generate panoramic image for sea environment because intensity is similar to all region and time varying. In this paper, we proposed new algorithm for generating high-resolution panoramic image on sea environment. Proposed algorithm use single-view point model, applying mosaicing result in feature environment to in sea environment, we overcame the limitation of previous method. In the result of virtual and real experiment, we showed that proposed algorithm is efficient for generating sea panoramic image.

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Content-based Image Retrieval Using Fuzzy Multiple Attribute Relational Graph (퍼지 다중특성 관계 그래프를 이용한 내용기반 영상검색)

  • Jung, Sung-Hwan
    • The KIPS Transactions:PartB
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    • v.8B no.5
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    • pp.533-538
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    • 2001
  • In this paper, we extend FARGs single mode attribute to multiple attributes for real image application and present a new CBIR using FMARG(Fuzzy Multiple Attribute Relational Graph), which can handle queries involving multiple attributes, not only object label, but also color, texture and spatial relation. In the experiment using the synthetic image database of 1,024 images and the natural image database of 1.026 images built from NETRA database and Corel Draw, the proposed approach shows 6~30% recall increase in the synthetic image database and a good performance, at the displacements and the retrieved number of similar images in the natural image database, compared with the single attribute approach.

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A Color Interpolation Method for Improved Edge Sensing (에지 선별을 개선한 컬러 보간법)

  • Cho, Yang-Ki;Kim, Hi-Seok
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.31 no.12C
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    • pp.1216-1223
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    • 2006
  • In many imaging devices, a single image sensor is used, which is covered by a color filter array to filter out the specific color components from light. Since an image acquired from this image sensors have a color components at each pixel, it is needed to be reconstructed to a perfect image. In this paper, a new color interpolation method for the imaging devices having a single image sensor is proposed. The proposed method improves a edge sensing function to obtain satisfactory results in edges of an image, md presents a new inter-channel correlation for improving interpolation performance in smooth region. We have compared our method with several exiting methods, and our experimental results have proved better interpolation performance in comparing with the other results.

Design of a Stereoscopic Image Display System Using a LCD Shutter (LCD 셔터를 이용한 입체 영상 디스플레이 시스템의 설계)

  • Lee, Ki-Jong;Kim, Nam-Jin;Moon, Jeong-Sueng;Kim, Ju-Young;Park, Gwi-Tae;Seo, Sam-Joon
    • Proceedings of the KIEE Conference
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    • 1998.11b
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    • pp.511-513
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    • 1998
  • This paper describes a full color stereoscopic video display system using a LCD shutter. Human apprehends the world with a natural stereo vision. The left eye sees through a slightly different perspective from the right eye; proposed vision system combines two images into a single image that has stereo depth. That is, when the left image is on the screen, the left shutter opens and the right shutter closes - and vice versa. The LCD shutter channels the left image to the left eye, and the right image to the right eye. The brain then fuses the stereo pair into a single high-resolution, flicker-free 3D image. The designed vision system is a real-time system that shows stereoscopic images without the loss of image information from video cameras.

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Jointly Learning of Heavy Rain Removal and Super-Resolution in Single Images

  • Vu, Dac Tung;Kim, Munchurl
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2020.11a
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    • pp.113-117
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    • 2020
  • Images were taken under various weather such as rain, haze, snow often show low visibility, which can dramatically decrease accuracy of some tasks in computer vision: object detection, segmentation. Besides, previous work to enhance image usually downsample the image to receive consistency features but have not yet good upsample algorithm to recover original size. So, in this research, we jointly implement removal streak in heavy rain image and super resolution using a deep network. We put forth a 2-stage network: a multi-model network followed by a refinement network. The first stage using rain formula in the single image and two operation layers (addition, multiplication) removes rain streak and noise to get clean image in low resolution. The second stage uses refinement network to recover damaged background information as well as upsample, and receive high resolution image. Our method improves visual quality image, gains accuracy in human action recognition task in datasets. Extensive experiments show that our network outperforms the state of the art (SoTA) methods.

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Fuzzy Single Layer Perceptron using Dynamic Adjustment of Threshold (동적 역치 조정을 이용한 퍼지 단층 퍼셉트론)

  • Cho Jae-Hyun;Kim Kwang-Baek
    • Journal of the Korea Society of Computer and Information
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    • v.10 no.5 s.37
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    • pp.11-16
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    • 2005
  • Recently, there are a lot of endeavor to implement a fuzzy theory to artificial neural network. Goh proposed the fuzzy single layer perceptron algorithm and advanced fuzzy perceptron based on the generalized delta rule to solve the XOR Problem and the classical Problem. However, it causes an increased amount of computation and some difficulties in application of the complicated image recognition. In this paper, we propose an enhanced fuzzy single layer Perceptron using the dynamic adjustment of threshold. This method is applied to the XOR problem, which used as the benchmark in the field of pattern recognition. The method is also applied to the recognition of digital image for image application. In a result of experiment, it does not always guarantee the convergence. However, the network show improved the learning time and has the high convergence rate.

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The Utility of Single Shot Turbo Spin Echo Technique for Temporal Bone Diffusion Weighted Imaging (관자뼈의 확산강조영상검사 시 Single Shot Turbo Spin Echo 기법의 유용성)

  • Choi, Kwan-Woo
    • Journal of radiological science and technology
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    • v.44 no.1
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    • pp.25-30
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    • 2021
  • The purpose was to reduce the distortion of the image that occurs in the temporal bone area due to the very strong differences in susceptibility. A new SS-TSE technique was applied when examining the diffusion-weighted image of the temporal bone, where the auditory and facial nerves to be imaged were very thin and were adjacent to the cranial base including bone and air. This study was conducted from March 2020 to August of the same year, targeting 32 subjects who underwent the diffusion-weighted imaging of the temporal bone. To compare the distortion, existing SS-EPI technique and the new SS-TSE technique were both applied on the temporal bone area. As a result of the study, applying the new SS-TSE technique appeared to lower the distortion of images by 87.44, 46.13 and 42.35 % on the b-value 0, 800 and the ADC images, respectively. In conclusion, when using the new SS-TSE technique on the temporal bone DWI, distortion can be reduced, and thus images with high diagnostic value can be obtained.

Image Translation of SDO/AIA Multi-Channel Solar UV Images into Another Single-Channel Image by Deep Learning

  • Lim, Daye;Moon, Yong-Jae;Park, Eunsu;Lee, Jin-Yi
    • The Bulletin of The Korean Astronomical Society
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    • v.44 no.2
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    • pp.42.3-42.3
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    • 2019
  • We translate Solar Dynamics Observatory/Atmospheric Imaging Assembly (AIA) ultraviolet (UV) multi-channel images into another UV single-channel image using a deep learning algorithm based on conditional generative adversarial networks (cGANs). The base input channel, which has the highest correlation coefficient (CC) between UV channels of AIA, is 193 Å. To complement this channel, we choose two channels, 1600 and 304 Å, which represent upper photosphere and chromosphere, respectively. Input channels for three models are single (193 Å), dual (193+1600 Å), and triple (193+1600+304 Å), respectively. Quantitative comparisons are made for test data sets. Main results from this study are as follows. First, the single model successfully produce other coronal channel images but less successful for chromospheric channel (304 Å) and much less successful for two photospheric channels (1600 and 1700 Å). Second, the dual model shows a noticeable improvement of the CC between the model outputs and Ground truths for 1700 Å. Third, the triple model can generate all other channel images with relatively high CCs larger than 0.89. Our results show a possibility that if three channels from photosphere, chromosphere, and corona are selected, other multi-channel images could be generated by deep learning. We expect that this investigation will be a complementary tool to choose a few UV channels for future solar small and/or deep space missions.

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The Study on Reduction of Image Distortion by using Single-Shot Turbo Spin Echo in Brain Stem Diffusion MRI (자기공명 확산강조영상검사 시 영상왜곡 감소에 관한 연구)

  • Choi, Kwan-Woo;Lee, Ho-Beom;Na, Sa-Ra;Yoo, Beong-Gyu;Son, Soon-Yong
    • Journal of the Korean Society of Radiology
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    • v.10 no.4
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    • pp.279-284
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    • 2016
  • Single-shot echo planar imaging(SS-EPI) is well established as high sensitivity for ischemic stroke. However, it is prone to susceptibility artifact in brain stem that diminish the image quality. single-shot turbo spin echo(SS-TSE) is a new DWI technique that can reduce susceptibility artifact. Thus, this research was conducted so as to reduce geometric distortion in brain stem by using single-shot turbo spin echo technique. Thirty patients without brain disease underwent diffusion MR on a 3T scanner with SS-EPI and SS-TSE. Obtained images with both sequences were analyzed for geometric distortion and error percentage as well. Image quality in terms of geometric distortion of SS-TSE were found to be significantly better than those for SS-EPI. And error percentage was considerably reduced for 2.4% of b0 image(from 11.1% to 8.7%), 1.2% of b1000 image(from 11.4% to 10.1%), respectively. In summary, diffusion MR using SS-TSE significantly reduce geometric distortion compared to SS-EPI in brain stem and may provide improved diagnostic performance.