• Title/Summary/Keyword: adaptive image decimation

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A Method for Estimating Local Intelligibility for Adaptive Digital Image Decimation (적응형 디지털 영상 축소를 위한 국부 가해성 추정 기법)

  • 곽노윤
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.4 no.4
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    • pp.391-397
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    • 2003
  • This paper is about the digital image decimation algorithm which generates a value of decimated element by an average of a target pixel value and a value of neighbor intelligible element to adaptively reflect the merits of ZOD method and FOD method on the decimated image. First, a target pixel located at the center of sliding window is selected, then the gradient amplitudes of its right neighbor pixel and its lower neighbor pixel are calculated using first order derivative operator respectively. Secondly, each gradient amplitude is divided by the summation result of two gradient amplitudes to generate each intelligible weight. Next, a value of neighbor intelligible element is obtained by adding a value of the right neighbor pixel times its intelligible weight to a value of the lower neighbor pixel times its intelligible weight. The decimated image can be acquired by applying the process repetitively to all pixels in input image which generates the value of decimated element by calculating the average of the target pixel value and the value of neighbor intelligible element.

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Performance Analysis of Adaptive Corner Shrinking Algorithm for Decimating the Document Image (문서 영상 축소를 위한 적응형 코너 축소 알고리즘의 성능 분석)

  • Kwak No-Yoon
    • Journal of Digital Contents Society
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    • v.4 no.2
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    • pp.211-221
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    • 2003
  • The objective of this paper is performance analysis of the digital document image decimation algorithm which generates a value of decimated element by an average of a target pixel value and a value of neighbor intelligible element to adaptively reflect the merits of ZOD method and FOD method on the decimated image. First, a target pixel located at the center of sliding window is selected, then the gradient amplitudes of its right neighbor pixel and its lower neighbor pixel are calculated using first order derivative operator respectively. Secondly, each gradient amplitude is divided by the summation result of two gradient amplitudes to generate each local intelligible weight. Next, a value of neighbor intelligible element is obtained by adding a value of the right neighbor pixel times its local intelligible weight to a value of the lower neighbor pixel times its intelligible weight. The decimated image can be acquired by applying the process repetitively to all pixels in input image which generates the value of decimated element by calculating the average of the target pixel value and the value of neighbor intelligible element. In this paper, the performance comparison of proposed method and conventional methods in terms of subjective performance and hardware complexity is analyzed and the preferable approach for developing the decimation algorithm of the digital document image on the basis of this analysis result has been reviewed.

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Design and Performance Analysis of Adaptive First-Order Decimator Using Local Intelligibility (국부 가해성을 이용한 적응형 선형 축소기의 설계 및 성능 분석)

  • Kwak, No-Yoon
    • Journal of Digital Contents Society
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    • v.9 no.1
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    • pp.17-26
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    • 2008
  • This paper has for its object to propose AFOD(Adaptive First-Order Decimator) which sets a value of decimated element as an average of a value of neighbor intelligible component and a output value of FOD(First-Order Decimator) for the target pixel, and to analyze its performance in terms of subjective image quality and hardware complexity. In the proposed AFOD, a target pixel located at the center of sliding window is selected first, then the gradient amplitudes of its right neighbor pixel and its lower neighbor pixel are calculated using first order derivative operator respectively. Secondly, each gradient amplitude is divided by the summation result of two gradient amplitudes to generate each local intelligible weight. Next, a value of neighbor intelligible component is defined by adding a value of the right neighbor pixel times its local intelligible weight to a value of the lower neighbor pixel times its intelligible weight. Since the proposed method adaptively reflects neighbor intelligible informations of neighbor pixels on the decimated element according to each local intelligible weight, it can effectively suppress the blurring effect being the demerit of FOD. It also possesses the advantages that it can keep the merits of FOD with the good results on average but also lower computational cost.

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