DOI: 10.1002/sdtp.16307 ISSN: 0097-966X

50.6: Establishing of the Device‐independent Mura Simulation and Quantitative Evaluation Dataset

Ming Wen, Xiaofan Feng, Zeng Qiang Zheng, Xiao Long Hu
  • General Medicine

There is a need to establish a novel dataset for the development of better Mura quantitative evaluation method. Our proposed Mura simulation and quantitative evaluation (MSQE) dataset consists of Mura simulation images and the corresponding quantitative evaluation values. For the Mura simulation images, the images are described in CIE 1931 XYZ space instead of traditional RGB space to achieve device‐independent on any display panels. For the quantitative evaluation values, the unique subjective quantitative evaluation value for each simulation image is obtained by subjective experiments conducted by different researchers, different observers, and on different panels, so that the uncertainty can be minimized by statistical analysis. The number of samples are growing with more simulation images and corresponding evaluation values being added into the dataset, so that more actual Mura patterns can be included into the dataset. Our proposed MSQE dataset makes it easier to improve the performance of Mura quantitative evaluation.

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