• Title/Summary/Keyword: Image convergence

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A Nonlinear Image Enhancement Method for Digital Mammogram (디지털 맘모그램을 위한 비선형 영상 향상 방법)

  • Jeon, Geum-Sang;Kim, Sang-Hee
    • Journal of the Institute of Convergence Signal Processing
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    • v.14 no.1
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    • pp.6-12
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    • 2013
  • Mammography is the most common technique for the early detection of breast cancer. To diagnose correctly and treat of breast cancer efficiently, many image enhancement methods have been developed. This paper presents a nonlinear image enhancement method for the enhancement of digital mammogram. The proposed method is composed of a nonlinear function for brightness improvement and a nonlinear filter for contrast enhancement. The nonlinear function improves the brightness of dark area and extends the dynamic range of bright area, and the nonlinear filter efficiently enhances the specific regions and objects of the mammogram. The final enhanced image was obtained by combining the processed image with the nonlinear function and the filtered image with the nonlinear filter. The proposed nonlinear image enhancement method was confirmed the enhanced performance comparing with other existing methods.

An Adaptive Image Enhancement of the DCT Compressed Image using the Spatial Frequency Property (공간주파수 특성을 이용한 DCT 압축영상의 적응 영상 향상)

  • Jeon, Seon-Dong;Kim, Sang-Hee
    • Journal of the Institute of Convergence Signal Processing
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    • v.11 no.2
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    • pp.104-111
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    • 2010
  • This paper presents an adaptive image enhancement method using the spatial frequency property in the DCT(discrete cosine transform) compressed domain. The dc coefficients, the illumination components of image, are adjusted to compress the dynamic range of image, and the ac coefficients are modified to enhance the contrast by using the human visual system(HVS) and the spatial frequency property. The ac coefficients are separated into vertical direction, horizontal direction, and mixed spatial frequency components, and adaptively modified to minimize the block artifacts that possibly occur in the image enhancement. The proposed method using dynamic range compression and adaptive contrast enhancement shows the advanced performance without the block artifact compared with existing method.

Correction of Single Photon Emission CT Image Distorted by Collimator Characteristic (시준기의 특성으로 인한 SPECT 왜곡 화상의 보정)

  • 백승권
    • Journal of the Institute of Convergence Signal Processing
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    • v.5 no.1
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    • pp.18-24
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    • 2004
  • SPECT technology is used for the reconstructed image in the field of industry noncontact measurement system. One of the distortion problems in reconstructed image quality is a collimator characterictic. The image distortion is caused by a geometrical structure of the collimator. This paper indicated a correction method to remove the image distortion by the structure of the collimator, and compared with the existing correction method. The correction. method removed the image distortion to use deconvolution of projection data with the shift-variant blurring function in the frequency domain. In this pater, I simulated with the collimator angle and distance between the detector and the center of object. and verified with expeimental data. The validity and limitation of correction method is studied for actual industrial applications.

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A Visual Reconstruction of Core Algorithm for Image Compression Based on the DCT (discrete cosine transform) (이산코사인변환 기반 이미지 압축 핵심 알고리즘 시각적 재구성)

  • Jin, Chan-yong;Nam, Soo-tai
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.10a
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    • pp.180-181
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    • 2018
  • JPEG is a most widely used standard image compression technology. This research introduces the JPEG image compression algorithm and describes each step in the compression and decompression. Image compression is the application of data compression on digital images. The DCT (discrete cosine transform) is a technique for converting a time domain to a frequency domain. First, the image is divided into 8 by 8 pixel blocks. Second, working from top to bottom left to right, the DCT is applied to each block. Third, each block is compressed through quantization. Fourth, the array of compressed blocks that make up the image is stored in a greatly reduced amount of space. Finally if desired, the image is reconstructed through decompression, a process using IDCT (inverse discrete cosine transform).

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A Study on the Enhancement of Image Distortion for the Hybrid Fractal System with SOFM Vector Quantizer (SOFM 벡터 양자화기와 프랙탈 혼합 시스템의 영상 왜곡특성 향상에 관한 연구)

  • 김영정;김상희;박원우
    • Journal of the Institute of Convergence Signal Processing
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    • v.3 no.1
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    • pp.41-47
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    • 2002
  • Fractal image compression can reduce the size of image data by the contractive mapping that is affine transformation to find the block(called as range block) which is the most similar to the original image. Even though fractal image compression is regarded as an efficient way to reduce the data size, it has high distortion rate and requires long encoding time. In this paper, we presented a hybrid fractal image compression system with the modified SOFM Vector Quantizer which uses improved competitive learning method. The simulation results showed that the VQ hybrid fractal using improved competitive loaming SOFM has better distortion rate than the VQ hybrid fractal using normal SOFM.

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The Stopped Vehicle Detection in the Tunnel Incident Surveillance System (터널 영상 유고 감지 시스템에서 정차 검출 알고리즘)

  • Kim, Gyu-Yeung;Lee, Geun-Hoo;Kim, Hyun-Tae;Kim, Jae-Ho;Yu, Yun-Sik
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2011.10a
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    • pp.607-608
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    • 2011
  • In this paper, we propose stopped vehicle detection algorithm in the tunnel. It is shown that our method distinguished objects from background estimated image, and then detected stopped vehicles efficiently based on the experimental analysis about the color information of their lamps. The simulation results show the detection rate is achieved over 95% in the tunnel image.

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Bio-Cell Image Segmentation based on Deep Learning using Denoising Autoencoder and Graph Cuts (디노이징 오토인코더와 그래프 컷을 이용한 딥러닝 기반 바이오-셀 영상 분할)

  • Lim, Seon-Ja;Vununu, Caleb;Kwon, Oh-Heum;Lee, Suk-Hwan;Kwon, Ki-Ryoug
    • Journal of Korea Multimedia Society
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    • v.24 no.10
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    • pp.1326-1335
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    • 2021
  • As part of the cell division method, we proposed a method for segmenting images generated by topography microscopes through deep learning-based feature generation and graph segmentation. Hybrid vector shapes preserve the overall shape and boundary information of cells, so most cell shapes can be captured without any post-processing burden. NIH-3T3 and Hela-S3 cells have satisfactory results in cell description preservation. Compared to other deep learning methods, the proposed cell image segmentation method does not require postprocessing. It is also effective in preserving the overall morphology of cells and has shown better results in terms of cell boundary preservation.

Generating 2D LEGO Instruction Manual Using Deep Learning Model (딥러닝 모델을 이용한 2D 레고 조립 설명서 생성)

  • Jongseok Ahn;Seunghyeon Lee;Cheolhee Kim;Donghee Kang
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2024.01a
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    • pp.481-484
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    • 2024
  • 본 논문에서는 레고(LEGO®) 조립 설명서를 생성하기 위해 딥러닝을 이용한 조립 및 설명서 생성 시스템을 제안한다. 이 시스템은 사용자가 제공한 단일 이미지를 기반으로 레고 조립 설명서를 자동 생성한다. 해당 시스템은 딥러닝 기반 이미지 분할 기술을 활용하여 물체를 배경으로부터 분리하고 이를 통해 조립 설명서를 생성하는 과정을 포함하며, 조립을 위한 알고리즘을 새로 설계하였다. 이 시스템은 기존 레고 제품의 한계를 극복하고, 사용자에게 주어진 부품으로 다양한 모델을 자유롭게 조립할 수 있게 한다. 또한, 복잡한 레고 조립 과정을 간소화하고, 조립의 장벽을 낮추는 데 도움을 준다.

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Fast Multiple Mixed Image Interpolation Method for Image Resolution Enhancement (영상 해상도 개선을 위한 고속 다중 혼합 영상 보간법)

  • Kim, Won-Hee;Kim, Jong-Nam;Jeong, Shin-Il
    • Journal of Broadcast Engineering
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    • v.19 no.1
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    • pp.118-121
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    • 2014
  • Image interpolation is a method of determining the value of new pixel coordinate in the process of image scaling. Recently, image contents are likely to be a large-capacity, interpolation algorithm is required to generate fast enhanced result image. In this paper, fast multiple mixed image interpolation for image resolution enhancement is proposed. The proposed method estimates expected 12 shortfalls from four sub-images of a input image, and generates the result image that is interpolated in the combination of the expected shortfalls with the input image. The experimental results demonstrate that PSNR increases maximum value of 1.9dB, SSIM increases maximum value of 0.052, and the subjective quality is superior to any other compared methods. Moreover, it is known by algorithm running time comparison that the proposed method has been at least three times faster than the compared conventional methods. The proposed method can be useful for application on image resolution enhancement.

Fast iterative image restoration algorithms based on preconditioning (전처리기를 사용한 반복적 영상복원의 고속화 기법)

  • 백준기;문준일;김상구
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.12
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    • pp.62-70
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    • 1996
  • Image restoration is the process which estimates the original image form the blurred image observed by the non-ideal imaging system with additivenoise. According to the regularized approach, the resotred image can be obtained by iterative methods or the constrained least square error(CLS) filter. Among those retoratin methods, despite of many advantages, iterative iamge restoration is limited in use because of slow convergence. In the present paper, fast iterative image restoration algorithms based on preconditoning are proposed. The preconditioner can be obtained by using the characteristics finite impulse response (FIR) filter structure.

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