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Dangers of Demosaicing: Confusion From Correlation

机译:脱染症的危险:相关性困惑

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摘要

Images from colour sensors using Bayer filter arrays require demosaicing before viewing or further analysis. Advanced demosaicing methods use empirical knowledge of inter-channel correlations to reduce interpolation artefacts in the resulting images. These inter-channel correlations are however different for standard RGB cameras and hyperspectral imagers using colour sensors with added narrow-band spectral filtering.We study the effects of conventional demosaicing methods on hyperspectral images with a dataset originally collected without a colour filter array. We find that using advanced methods instead of bilinear interpolation results in an overall increase of 9-14% in absolute error and a decrease of 1-3% in PSNR, but also observed a decrease in MSE of 11-13%.For the corresponding RGB images, the advanced methods improved fidelity as expected. The results also demonstrate that the reconstruction methods that take advantage of correlation transport noise present in a single component to other reconstructed layers.
机译:使用拜耳滤波器阵列的颜色传感器的图像在查看或进一步分析之前需要去脱模。先进的去脱索方法使用频道间相关性的经验知识,以减少所产生的图像中的插值伪影。然而,标准RGB摄像机和高光谱成像器的这些通道间相关性不同,使用具有添加的窄带谱滤波的颜色传感器。我们研究了在没有滤色器阵列的情况下收集的数据集对高光谱图像对高光谱图像的影响。我们发现,使用先进的方法而不是双线性插值导致绝对误差的总体增加9-14%,PSNR中的1-3%降低,但也观察到MSE的减少11-13%。相应的RGB图像,高级方法按预期提高了保真度。结果还表明,重建方法,其利用在单个组件中存在于其他重建层的相关传输噪声。

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