J. Yang’s scientific contributions

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Publications (2)


Research of accurate control color of CRT display in small range
  • Article

July 2007

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13 Reads

J. Yang

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J.-S. Shi

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X.-Q. Huang

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J.-C. Yao

The present accuracy of CRT characterization is about 0.5ΔE* ab. In some experiments of measurement of color difference, color appearance, image appearance, contrast sensitivity function, accurate control color in small range around color centers is necessary. A method of color control in experiment is presented, which adopts the linear interpolation and takes into account the interaction of three channels in small range. With this method, the experimental results show that characterization accuracies are 0.14, 0.082, 0.103 for L*, a*, b* respectively, and 0.18, 0.18, 0.22 for three kinds of color differences of CIELAB, CIE94, CIEDE2000.


Study on color image quality evaluation by MSE and PSNR based on color difference

June 2007

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358 Reads

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16 Citations

The performance of an image quality evaluation model can be improved by considering characteristics of the human visual system. The S-CIELAB model, which takes account of the spatial blurring by human visual system, is used to measure color difference between two color images. In this paper, it presents that the two parameters of objective evaluation of color image quality, color difference mean square error (CD-MSE) and color difference peak signal-to-noise ratio (CD-PSNR) based on the model of S-CIELAB. Objective experiments are conducted on three kinds of distorted images of JEPG2000, white Gaussian noise and transmission errors in JPEG2000 bitstream (total 180 images), compared with subjective evaluation of mean opinion score (MOS), and results show consistency between them.

Citations (1)


... In research of objective quality evaluation, the objective metrics for traditional 2D LDR images have been studied for the earliest time and achieved series of well-performed results. Specifically, there are classical image quality metrics (IQMs) based on pixel error, such as PSNR and MSE [7], and metrics that take the factors of image structure, visual perception, and statistical characteristics into account, such as SSIM [8], NIQE [9], BRISQUE [10], SSEQ [11], and so on. However, with the increase of the FOV, the perceptual mechanism of visual system works differently with traditional visual contents [12]. ...

Reference:

No-Reference High Dynamic Range Omnidirectional Image Quality Metric: From the Perspective of Global and Local Statistical Characteristics
Study on color image quality evaluation by MSE and PSNR based on color difference
  • Citing Article
  • June 2007