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Self-Healing Imager Based on Detection and Conciliation of Defective Pixels

机译:基于缺陷像素的检测和调解的自愈成像仪

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This paper presents imager self-healing method based on detection and correction of defective pixels in the produced image file. The proposed method uses a neighborhood analysis with simple arithmetic operations including distance between the to-be-tested pixel and its neighbor pixels. A 2-dimensional 3 by 3 gray-scale image matrix around the to-be-tested pixel is used to estimate an expected pixel value and a weighted average. This average value is used as an adaptive threshold of the difference value between expected and actual pixel values. The performances in terms of sensibility, specificity, predictive values, and phi-coefficient of the produced results on a set of 144 distorted images (24 references images x 6 distortion types), are compared to another dead pixel detection methods performances. Experimental results demonstrated that our proposal produces the best results.
机译:本文基于检测和校正产生的图像文件中的缺陷像素的图像仪自我修复方法。所提出的方法使用邻域分析,简单的算术运算包括待测像素与其邻居像素之间的距离。待测像素周围的3次灰度图像矩阵的2维3用于估计预期的像素值和加权平均值。该平均值用作预期和实际像素值之间的差值的自适应阈值。与另一种死像素检测方法的性能进行比较,在一组144扭曲图像上对所产生的结果的敏感性,特异性,预测值和PHI系数的性能进行比较(24参考图像x 6失真类型)。实验结果表明,我们的提案产生了最佳效果。

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