• Title/Summary/Keyword: Error diffusion method

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RELATIONSHIP BETWEEN ERROR DIFFUSION COEFFICIENTS, OBJECT SIZE AND OBJECT POSITION FOR CGH

  • Nishi, Susumu;Tanaka, Ken-ichi
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2009.01a
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    • pp.492-497
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    • 2009
  • Computer-Generated Hologram (CGH) is made for three dimensional image of a virtual object. Error diffusion method is used for the phase quantization of CGH, and it is known to be effective to the image quality improvement of the reconstructed image. However, the image quality of the reconstructed image from the CGH using error diffusion method depends on the selection of error diffusion coefficient. In this paper, we derived the relational expression to obtain the error diffusion coefficient from the position of the input object and size of the input object for CGH. As a result, the method of this thesis was able to obtain an excellent reconstructed image compared with the case to derive the error diffusion coefficient from only the position of the input image.

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IMPROVEMENT OF COLOR HALFTONING USING ERROR DIFFUSION METHOD

  • Takahashi, Yoshiaki;Tanaka, Ken-Ichi
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2009.01a
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    • pp.516-519
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    • 2009
  • In the printer and the facsimile communication, digital halftoning is extremely important technologies. Error diffusion method is applied easy for color image halftoning. But the problem in error diffusion method is that a quite unrelated color has been generated though it is necessary to express the area of the grayscale in the black and white when the image that there is an area of the grayscale on a part of the color image is processed. The halftoning was assumed to be a combinational optimization problem to solve this problem, and the method of using SA (Simulated Annealing) was proposed. However, new problem existed because the processing time was a great amount compared with error diffusion method. Then, we propose the new error diffusion method.

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Truncation Error Problem of Error Diffusion Method (오차 확산 방법의 절삭 오차 문제)

  • Jho, Cheung-Woon
    • Journal of Advanced Navigation Technology
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    • v.15 no.5
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    • pp.850-856
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    • 2011
  • The error diffusion method is one of the digital halftoning methods that diffuses quantization errors of current processing pixel to neighboring pixels and get a high-quality black-white image. This method has the problematic case which partially increase or decrease summation of diffused errors in the process of diffusing the quantization error. In this paper, we analyze Floyd-Steinberg method, Jarvis-Judice-Ninke method, Stucki method, and Shiau-Fan method as a representative case of error diffusion methods and propose a solution method of this problem.

Edge Enhanced Error Diffusion based on Gradient Shaping of Original Image (원영상의 기울기 성형을 이용한 경계강조 오차확산법)

  • 강태하
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.10B
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    • pp.1832-1840
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    • 2000
  • The error diffusion algorithm is good for reproducing continuous images to binary images. However the reproduction of edge characteristics is weak in power spectrum an analysis of display error. In this paper an edge enhanced error diffusion method is proposed to improve the edge characteristic enhancement. Spatial gradient information in original image is adapted for edge enhance in threshold modulation of error diffusion. First the horizontal and vertical second order differential values are obtained from the gradient of peripheral pixels(3x3) in original image. second weighting function is composed by function including absolute value and sign of second order differential values. The proposed method presents a good visual results which edge characteristics is enhanced. The performance of the proposed method is compared with that of the conventional edge enhanced error diffusion by measuring the edge correlation and the local average accordance over a range of viewing distances and the RAPSD of display error.

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The Edge Enhanced Error Diffusion Using Local Characteristic Weights (국부적 특성 가중치를 이용한 에지 강조 오차 확산 방법)

  • 곽내정;윤태승;유성필;안재형
    • Proceedings of the IEEK Conference
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    • 2003.11a
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    • pp.381-384
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    • 2003
  • Among digital halftoning methods, error diffusion is a procedure for generating high quality bilevel images from continuous-tone images but blurs the edge information in the bilevel images. To solve the problem, we propose the edge enhanced error diffusion using the edge information of the original images. The edge enchanted weights is computed by adding local characteristic weights and input pixels multiplied a constant. Also, we combined the edge enhanced method with the adaptive error diffusion using human spatial and frequency perception characteristic. The performance of the proposed method is compared with conventional method by measuring the edge correlation. The halftoned images applied the proposed method get more fine quality due to the enchanced edge and better quality in halftoned image. And the detailed edge is preserved in the halftoned images by the proposed method.

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Error Diffusion Using an Adaptive Threshold (적응형 임계값을 이용한 오차확산 방법)

  • Kwon Jun-Sik;Lee Jae-Young;Park You-Shin
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.43 no.1 s.307
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    • pp.17-26
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    • 2006
  • The error diffusion method is one of the digital halftoning processes that transforms the continuous-tone image to the binary image and the method has the excellent reproduction ability. However the error diffusion method using the permanent threshold has difficulty in proper binarization, so the method has the periodic pattern and is unpleasant to the eye. In this paper, to reduce defects and to binarize properly, we propose the error diffusion method using the adaptive threshold. Depending on the intensity distribution of the input gray scale image, we decided on the adaptive threshold with the average of the intensities. The error diffusion method with the adaptive threshold has the better performance than the existing method and is evaluated with experiments and comparisons.

Edge Enhanced Error Diffusion Based on Local Average of Original Image

  • Kang, Tae-Ha;Lee, Tae-Seung;Park, Hyeong-Taek;Hwang, Byong-Won
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.612-615
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    • 2003
  • The error diffusion is a good method to reconstruct the continuous tones of an image to the bilevel tones However the reconstruction of edge characteristic by the nor diffusion is represented work when power spectrum is analyzed fer display error. In this paper, we present an edge enhanced error diffusion method to preprocess original image to achieve the enhancement for the edge characteristic. The preprocessing algorithm consist of two processes. First the difference value between the current pixel and the local average of the surrounding pixel in original image is obtained. Second, the weighting function is composed by the magnitude and the sign of the local average. To confirm the effect of the proposed method, it is compared with the conventional edge enhanced error diffusion methods by measuring the radially averaged power spectrum densities (RAPSDs) for their display errors. The comparison result demonstrate the superiority of the proposed method over the conventional ones.

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Edge Enhanced Error Diffusion based on Gradient Shaping of Original image (원영상의 기울기 성형을 이용한 경계강조 오차확산법)

  • 강태하;황병원
    • Proceedings of the IEEK Conference
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    • 2000.06d
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    • pp.70-73
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    • 2000
  • The error diffusion is good for reproducing continuous image to binary image. However the reproduction of edge characteristics is weak in power spectrum analysis of display error. It is suggested for us an edge-enhanced error-diffusion method that is included pre-processing algorithm for edge characteristic enhancement. Pre-processing algorithm is organized horizontal and vertical directional 2nd order differential values and weighting function of pre-filter. The improved Error diffusion using pre-filter, presents a good results visually which edge characteristics is enhanced. The performance of the proposed algorithm is compared with that of the conventional edge-enhanced error diffusion by measuring the RAPSD of display error, the egde correlation and the local average accordance.

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Multi-level Vector Error Diffusion for Smear Artifact Reduction in the Boundary Regions (경계 영역에서 색 번짐 감소를 위한 멀티레벨 벡터 오차 확산법)

  • 박태용;조양호;김윤태;하영호
    • Proceedings of the IEEK Conference
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    • 2003.11a
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    • pp.461-464
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    • 2003
  • This paper proposes the multi-level vector error diffusion for smear artifact reduction in the boundary regions. Smear artifact mainly results from a large accumulation of quantization error. Accordingly, to reduce these artifacts, the proposed method excludes the large quantization error in the error diffusion process by comparing the magnitude of the error vector with predetermined first threshold. In addition, if the vector norm of the difference between the error adjusted input vector and the primary co]or that has minimum vector norm for the error adjusted input vector is larger than second threshold, the error is excluded. As a result, the proposed method reduce smear artifact in the boundary region and produces visually pleasing halftone pattern.

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Fast multilevel vector error diffusion based on adaptive selection of patch (적응적 패치 선택에 기반한 고속 멀티레벨 벡터 오차 확산법)

  • 박태용;이명영;조양호;하영호
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.1747-1750
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    • 2003
  • This paper proposes a multilevel vector error diffusion for fast and accurate color reproduction. Proposed method considered both hue angle and Euclidean distance during the multilevel vector error diffusion procedure to improve time complexity and output image quality In the error diffusion process, it can be determined whether error is diffused or not by comparing the vector norm and lightness value between original vector and error corrected vector of neighborhood pixels. For adaptive selection of output patch, this paper computes chroma value of error corrected vector and compares the hue angle between error corrected input vector and 64 primary color vectors.

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