Due to the latest progress in image sensor manufacturing technology, the emergence of a sensor equipped with an RGGB Bayer filter and a directional polarizing filter has brought significant advantages to computer vision tasks where RGB and polarization information is required. In this regard, joint chromatic and polarimetric image demosaicing is indispensable. However, as a new type of array pattern, there is no dedicated method for this challenging task. In this Letter, we collect, to the best of our knowledge, the first chromatic-polarization dataset and propose a chromatic-polarization demosaicing network (CPDNet) to address this joint chromatic and polarimetric image demosaicing issue. The proposed CPDNet is composed of the residual block and the multi-task structure with the costumed loss function. The experimental results show that our proposed methods are capable of faithfully recovering full 12-channel chromatic and polarimetric information for each pixel from a single mosaic image in terms of quantitative measures and visual quality.

中文翻译：

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用于联合色度和偏振图像的卷积去马赛克网络

由于图像传感器制造技术的最新进展，配备了RGGB拜耳滤光片和定向偏振滤光片的传感器的出现为需要RGB和偏振信息的计算机视觉任务带来了显着优势。在这方面，联合色差和偏振图像去马赛克是必不可少的。但是，作为一种新型的阵列模式，没有专门的方法来完成这一具有挑战性的任务。在本信中，我们尽我们所知收集了第一个色偏振数据集，并提出了一个色偏振去马赛克网络（CPDNet），以解决这个联合的色偏振图像去马赛克问题。所提出的CPDNet由残差块和具有损失函数的多任务结构组成。