• Title/Summary/Keyword: 이미지 선명화

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Advanced Retinex Algorithm for Image Enhancement (영상 선명화를 위한 개선된 Retinex 알고리즘)

  • Cha, Hyo-Sang;Hong, Sung-Hoon
    • Journal of Korea Multimedia Society
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    • v.16 no.1
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    • pp.29-41
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    • 2013
  • The digital camera is impossible to preserve the appearance of a scene containing high dynamic range due to a limitations of the sensing hardware. The Retinex was proposed on the purpose to solve these problems. While the Retinex enhances visibility and color constancy, it sometimes suffers from color distortion, halo effect and reduced global contrast. This paper presents an advanced Retinex algorithm working on the YCbCr color coordinate to reduce the processing time and to improve the global contrast and color. Simulation results show that our algorithm significantly reduces the total processing time, and provide the superior result image by improving the global contrast and color consistency as well as by reducing the halo effect around the boundaries.

An Efficient Segmentation System for Cell Images By Classifying Distributions of Histogram (히스토그램 분포 분류를 통한 효율적인 세포 이미지 분할 시스템)

  • Cho, Migyung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.2
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    • pp.431-436
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    • 2014
  • Cell segmentation which extracts cell objects from background is one of basic works in bio-imaging which analyze cell images acquired from live cells in cell culture. In the case of clear images, they have a bi-modal histogram distribution and segmentation of them can easily be performed by global threshold algorithm such as Otsu algorithm. But In the case of degraded images, it is difficult to get exact segmentation results. In this paper, we developed a cell segmentation system that it classify input images by the type of their histogram distribution and then apply a proper segmentation algorithm. If it has a bi-modal distribution, a global threshold algorithm is applied for segmentation. Otherwise it has a uni-modal distribution, our algorithm is performed. By experimentation, our system gave exact segmentation results for uni-modal cell images as well as bi-modal cell images.

Image Reconstruction Using Poisson Model Screened from Image Gradient (이미지 기울기에서 선별된 포아송 모델을 이용한 이미지 재구성)

  • Kim, Yong-Gil
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.18 no.2
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    • pp.117-123
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    • 2018
  • In this study, we suggest a fast image reconstruction scheme using Poisson equation from image gradient domain. In this approach, using the Poisson equation, a guided vector field is created by employing source and target images within a selected region at the first step. Next, the guided vector is used in generating the result image. We analyze the problem of reconstructing a two-dimensional function that approximates a set of desired gradients and a data term. The joined data and gradients are able to work like modifying the image gradients while staying close to the original image. Starting with this formulation, we have a screened Poisson equation known in physics. This equation leads to an efficient solution to the problem in FFT domain. It represents the spatial filters that solve the two-dimensional screened Poisson model and shows gradient scaling to be a well-defined sharpen filter that generalizes Laplace sharpening. We demonstrate the results using a discrete cosine transformation based this Poisson model.

A Study on the Stereo Matching which using an Edge-Adaptive Method (에지 적응형 방법을 이용한 스테레오 정합에 관한 연구)

  • Han, Ki-Seo;Yeom, Jin-Su;Hur, Chnag-Wo;Ryu, Kwang-Ryol
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2007.06a
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    • pp.164-167
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    • 2007
  • 스테레오 정합을 하기 위해서 먼저 두 이미지의 자기를 정규화 하였고, 밝기가 정규화 된 영상을 이용하여 Canny방식으로 Edge를 검출한 후 에지 적응형 스테레오 정합 방식으로 두 영상을 정합하여 변이도 영상들을 얻었다. 그 중 Canny Edge 방식이 다른 Edge 검출 방식보다 선명한 영상을 추출했다. Canny Edge 방식으로 획득한 스테레오영상을 중위수 필터를 사용하여 잡음을 제거한 후, 필터링 전 후의 영상을 PSNR(Peak Signal to Noise Ratio)로 비교하여 본 결과 개선된 영상을 획득 하였다.

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Deep Learning based Color Restoration of Corrupted Black and White Facial Photos (딥러닝 기반 손상된 흑백 얼굴 사진 컬러 복원)

  • Woo, Shin Jae;Kim, Jong-Hyun;Lee, Jung;Song, Chang-Germ;Kim, Sun-Jeong
    • Journal of the Korea Computer Graphics Society
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    • v.24 no.2
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    • pp.1-9
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    • 2018
  • In this paper, we propose a method to restore corrupted black and white facial images to color. Previous studies have shown that when coloring damaged black and white photographs, such as old ID photographs, the area around the damaged area is often incorrectly colored. To solve this problem, this paper proposes a method of restoring the damaged area of input photo first and then performing colorization based on the result. The proposed method consists of two steps: BEGAN (Boundary Equivalent Generative Adversarial Networks) model based restoration and CNN (Convolutional Neural Network) based coloring. Our method uses the BEGAN model, which enables a clearer and higher resolution image restoration than the existing methods using the DCGAN (Deep Convolutional Generative Adversarial Networks) model for image restoration, and performs colorization based on the restored black and white image. Finally, we confirmed that the experimental results of various types of facial images and masks can show realistic color restoration results in many cases compared with the previous studies.

A Parallel Implementation of JPEG2000 4K Ultra High Definition Image using OpenCL (OpenCL을 이용한 JPEG2000 4K 초고화질 영상처리의 병렬고속화 구현)

  • Park, Daeseung;Kim, Cheong Ghil
    • Journal of Satellite, Information and Communications
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    • v.10 no.1
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    • pp.1-5
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    • 2015
  • With the help of fast growing multimedia technology and high preference for users of large screens, the newest video coding standard, HEVC (High Efficiency Video Coding) high-quality video compression), has been introduced. Therefore, the high definition image services which are four times more clear than conventional HD video, are getting popular. JPEG 2000 also has stated to support 4K and 8K UHD. As a result, it requires fast processing technology to read and write UHD images. This paper introduces a study on fast parallel processing technology for UHD images. For this purpose, first, JPEG 2000 is reviewed and a GPU based parallel implementation is proposed for a preprocessing of color conversion stage. The parallelled algorithm is implemented with OpenCL (Open Computing Language). The simulation results show that the proposed method shows 5 times performance improvements on processing speed for 4K UHD over the method using threads.

Measurement of the Flow Field in a River (LSPIV에 의한 하천 표면유속장의 관측)

  • Kim, Young-Sung;Yang, Jae-Rheen
    • Proceedings of the Korea Water Resources Association Conference
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    • 2009.05a
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    • pp.1812-1816
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    • 2009
  • 이미지 해석에 의한 유속장 측정방법은 유체역학분야에서 지난 30 여년 동안 많이 활용되어온 속도측정 기법으로 오늘날에는 이를 수공학 분야에서 이를 유량측정 등 수리현상 해석에 활용하려는 시도가 다각적으로 이루어지고 있다. 이에 본 연구에서는 이미지 해석에 의한 유속장 측정방법을 용담댐 시험유역에 적용하여 그의 자연하천에서의 적용성을 검토하고자 한다. 이미지 해석에 의한 유속장 측정방법은 PIV(Particle Image Velocimetry)로 통칭되고 있으며, PIV는 seeding, illumination, recording, 및 image processing의 네 가지 요소로 구성된다. seeding을 위해서 유체를 따라 흐를수 있는 작은 입자를 유체에 첨가한다. 유체를 따라 흐르는 입자들의 선명한 이미지를 얻기 위해서illumination이 필요하다. PIV를 이용하여 흐름을 해석하기 위한 illumination은 일반적으로 이중펄스 레이저가 이용된다. 이렇게 유속장 해석을 하려는 유체에 대하여 seeding 및 illumination이 준비되면 단일노출- 다중 프레임법, 혹은 다중노출-단일 프레임법으로 흐름을 recording을 한다. image processing은 이미지를 다운로드하고, 디지타이징 및 화질향상을 하는 전처리(pre-processing), 상관계수의 산정에 의한 유속 벡터의 결정 및 에러 벡터를 제거하고 유속장을 그래프화하는 후처리(post-processing) 과정으로 구성된다. LSPIV(Large Scale PIV)는 PIV의 기본원리를 근거로 하여 기존의 PIV에 비하여 실험실 내에서의 수리모형실험이나 일반 하천에서의 유속측정과 같은 큰 규모$(4m^2\sim45,000m^2$)의 흐름해석을 할 수 있도록 Fujita et al.(1994)와 Aya et al.(1995)이 확장시킨 것이다. PIV와 비교시 LSPIV의 다른 점은 넓은 흐름 표면적을 포함하기 위하여 촬영시에 카메라의 광축과 흐름 사이의 각도가 PIV에서 이용하는 수직이 아닌 경사각을 이용하였고 이에 따라 발생하는 이미지의 왜곡을 제거하기 위하여 이미지 변환기법을 적용하여 왜곡이 없는 정사촬영 이미지로 변환시킨다. 이후부터는 PIV의 이미지 처리 방법이 적용되어 표면유속을 산정한다. 다만 이미지 변환을 PIV 이미지 처리 전에 하느냐 후에 하느냐에 따라 유속장 해석결과에 차이가 있다. PIV의 네가지 단계를 포함하여 LSPIV의 각 단계를 구분하면, seeding, illumination, recording, image transformation,image processing 및 post-processing의 여섯 단계로 나뉘어진다 (Li, 2002). LSPIV를 적용시 물표면 입자의 Tracing을 위하여 자연하천에서 사용하기에 적합한 환경친화적인 seeding 재료인 Wood Mulch를 사용하여 유속을 측정하였다. 적용지점은 용담댐 상류의 동향수위관측소 지점으로 이 지점은 한국수자원공사의 수자원시험유역이 위치하고 있다. 이미지의 촬영은 가정용 비디오 캠코더 (Sony DCR-PC 350)을 이용하여 두 줄기의 흐름에 대하여 각각 약 5분 동안의 영상을 촬영한후 이중에서 seeding의 분포가 잘 이루어진 약 1분간을 추출한후 이를 이용하여 PIV 분석에 이용하였다. 대체적으로 유속장의 계산이 무난하게 이루어지었으나 비교적 수질 상태가 양호하고, 수심이 낮고, 하상재료가 자갈로 이루어져 있어 비슷한 색상의 seeding 재료를 추적하기 어려운 구간이 발생한 부분에서는 유속의 계산이 정확히 이루어지지 않았다.

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Analysis of emotional images according to eyes shapes and smoky makeup tone (눈 형태에 따른 스모키 메이크업의 감성 이미지)

  • Kim, Min-Kyung;Ryu, Hee-Wook
    • Science of Emotion and Sensibility
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    • v.14 no.2
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    • pp.321-330
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    • 2011
  • Images of smoky make up illustrations with different the brightness tones for typical Korean eyes (standard one, small single eyelid and tailed up style) were systematically analyzed using vision-based emotional descriptive language for students majoring makeup and professional group. We identified that various images could be expressed by changing smoky makeup tones on eyes types through analysis of the emotional descriptive language. The smoky make up image recognition of smoky make up illustrations was almost consistent between the students and the professional group, but there was the distinct difference of image perception by two groups for some smoky make up illustrations due to the generation gap as well as their make up expertise and techniques. We suggested the image positioning maps which expressed the emotional reaction felt according to eyes shapes and smoky make up tones. The positioning maps were to provide criteria for various images to be able to express by smoky make up.

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K-means clustering using a center of gravity for grid-based sample (그리드 기반 표본의 무게중심을 이용한 케이-평균군집화)

  • Lee, Sun-Myung;Park, Hee-Chang
    • Journal of the Korean Data and Information Science Society
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    • v.21 no.1
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    • pp.121-128
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    • 2010
  • K-means clustering is an iterative algorithm in which items are moved among sets of clusters until the desired set is reached. K-means clustering has been widely used in many applications, such as market research, pattern analysis or recognition, image processing, etc. It can identify dense and sparse regions among data attributes or object attributes. But k-means algorithm requires many hours to get k clusters that we want, because it is more primitive, explorative. In this paper we propose a new method of k-means clustering using a center of gravity for grid-based sample. It is more fast than any traditional clustering method and maintains its accuracy.

Optimal Design Space Exploration of Multi-core Architecture for Real-time Lane Detection Algorithm (실시간 차선인식 알고리즘을 위한 최적의 멀티코어 아키텍처 디자인 공간 탐색)

  • Jeong, Inkyu;Kim, Jongmyon
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.7 no.3
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    • pp.339-349
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    • 2017
  • This paper proposes a four-stage algorithm for detecting lanes on a driving car. In the first stage, it extracts region of interests in an image. In the second stage, it employs a median filter to remove noise. In the third stage, a binary algorithm is used to classify two classes of backgrond and foreground of an input image. Finally, an image erosion algorithm is utilized to obtain clear lanes by removing noises and edges remained after the binary process. However, the proposed lane detection algorithm requires high computational time. To address this issue, this paper presents a parallel implementation of a real-time line detection algorithm on a multi-core architecture. In addition, we implement and simulate 8 different processing element (PE) architectures to select an optimal PE architecture for the target application. Experimental results indicate that 40×40 PE architecture show the best performance, energy efficiency and area efficiency.