用双摄协同提升多光谱图像去马赛克精度。
Multispectral Demosaicing via Dual Cameras
- 利用高分辨率RGB图像指导低分辨率多光谱图像的重建
- 在自建双摄数据集上实现当前最优去马赛克效果
- 适合手机等移动设备上的多光谱成像应用
多光谱（MS）图像在广阔光谱波段捕捉场景细节，对需要丰富光谱信息的应用至关重要。将多光谱成像集成到智能手机等多摄像头设备中，有望同时提升光谱应用性能与RGB图像质量。处理多光谱数据的关键步骤是去马赛克，即从相机捕获的马赛克多光谱图像中重建颜色信息。本文提出一种专为双摄像头系统设计的多光谱图像去马赛克方法，其中RGB和多光谱相机同时拍摄同一场景。该方法利用空间分辨率更高的共捕获RGB图像，引导低分辨率多光谱图像的去马赛克过程。我们构建了首个大规模双摄数据集Dual-camera RGB-MS Dataset，包含配对的RGB与多光谱马赛克图像及其真实值去马赛克结果，支持模型训练与评估。实验表明，所提方法在多个指标上优于现有技术。
原文摘要 · Abstract (English)
Multispectral (MS) images capture detailed scene information across a wide range of spectral bands, making them invaluable for applications requiring rich spectral data. Integrating MS imaging into multi camera devices, such as smartphones, has the potential to enhance both spectral applications and RGB image quality. A critical step in processing MS data is demosaicing, which reconstructs color information from the mosaic MS images captured by the camera. This paper proposes a method for MS image demosaicing specifically designed for dual-camera setups where both RGB and MS cameras capture the same scene. Our approach leverages co-captured RGB images, which typically have higher spatial fidelity, to guide the demosaicing of lower-fidelity MS images. We introduce the Dual-camera RGB-MS Dataset - a large collection of paired RGB and MS mosaiced images with ground-truth demosaiced outputs - that enables training and evaluation of our method. Experimental results demonstrate that our method achieves state-of-the-art accuracy compared to existing techniques.
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