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Generic MSFA Mosaicking and Demosaicking for Multispectral Cameras

机译:适用于多光谱相机的通用MSFA镶嵌和去马赛克

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摘要

In this paper, we investigate the potential application of the multispectral filter array (MSFA) techniques in multispectral imaging for reasons like low cost, exact registration, and strong robustness. In both human and many animal visual systems, different types of photoreceptors are organized into mosaic patterns. This behavior has been emulated in the industry to develop the so-called color filter array (CFA) in the manufacture of digital color cameras. In this way, only one color component is measured at each pixel, and the sensed image is a mosaic of different color bands. We extend this idea to multispectral imaging by developing generic mosaicking and demosaicking algorithms. The binary tree-driven MSFA design process guarantees that the pixel distributions of different spectral bands are uniform and highly correlated. These spatial features facilitate the design of the generic demosaicking algorithm based on the same binary tree, which considers three interrelated issues: band selection, pixel selection and interpolation. We evaluate the reconstructed images from two aspects: better reconstruction and better target classification. The experimental results demonstrate that the mosaicking and demosaicking process preserves the image quality effectively, which further supports that the MSFA technique is a feasible solution for multispectral cameras.
机译:在本文中,由于成本低,精确配准和鲁棒性强等原因,我们研究了多光谱滤镜阵列(MSFA)技术在多光谱成像中的潜在应用。在人类和许多动物视觉系统中,不同类型的感光器都被组织成马赛克图案。在业界已经模拟了这种行为,以开发数字彩色相机制造中的所谓彩色滤光片阵列(CFA)。以此方式,在每个像素处仅测量一个颜色分量,并且所感测的图像是不同色带的马赛克。通过开发通用的镶嵌算法和去马赛克算法,我们将该思想扩展到多光谱成像。二叉树驱动的MSFA设计过程可确保不同光谱带的像素分布均匀且高度相关。这些空间特征有助于基于相同二叉树的通用去马赛克算法的设计,该算法考虑了三个相互关联的问题:频带选择,像素选择和插值。我们从两个方面评估重建的图像:更好的重建和更好的目标分类。实验结果表明,镶嵌和去马赛克过程可以有效地保持图像质量,这进一步证明了MSFA技术是多光谱相机的可行解决方案。

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