SASSI — Super-Pixelated Adaptive Spatio-Spectral Imaging
SASSI — Super-Pixelated Adaptive Spatio-Spectral Imaging
复制标题
DOI：
10.1109/tpami.2021.3075228
复制
发表时间：
2020-12
影响因子：
23.6
通讯作者：
Vishwanath Saragadam;Michael DeZeeuw;Richard Baraniuk;A. Veeraraghavan;Aswin C. Sankaranarayanan
中科院分区：
文献类型：
--
作者：
Vishwanath Saragadam;Michael DeZeeuw;Richard Baraniuk;A. Veeraraghavan;Aswin C. Sankaranarayanan
本文介绍了一种新型的高分辨率视频超光谱成像仪，它具有高的空间、时间和光谱分辨率。我们的关键假设是，每个超像素内的像素的光谱轮廓往往是相似的。因此，场景自适应空间采样的高光谱场景，其超像素分割图像的指导下，能够获得高质量的重建。为了实现这一点，我们获取场景的RGB图像，计算其超像素，从中我们生成测量高分辨率光谱的位置的空间掩模。高光谱图像随后估计融合的RGB图像和光谱测量使用可学习的引导滤波方法。由于超像素估计步骤的计算复杂度较低，我们的设置可以捕获场景的高光谱图像，与传统的快照高光谱相机相比开销很小，但具有显着更高的空间和光谱分辨率。我们验证了所提出的技术与广泛的模拟，以及实验室原型，测量高光谱视频的空间分辨率为600 ×900 × 600 ×900像素，在可见光波段的光谱分辨率为10 nm，并实现在18 fps的帧速率。
We introduce a novel video-rate hyperspectral imager with high spatial, temporal and spectral resolutions. Our key hypothesis is that spectral profiles of pixels within each super-pixel tend to be similar. Hence, a scene-adaptive spatial sampling of a hyperspectral scene, guided by its super-pixel segmented image, is capable of obtaining high-quality reconstructions. To achieve this, we acquire an RGB image of the scene, compute its super-pixels, from which we generate a spatial mask of locations where we measure high-resolution spectrum. The hyperspectral image is subsequently estimated by fusing the RGB image and the spectral measurements using a learnable guided filtering approach. Due to low computational complexity of the superpixel estimation step, our setup can capture hyperspectral images of the scenes with little overhead over traditional snapshot hyperspectral cameras, but with significantly higher spatial and spectral resolutions. We validate the proposed technique with extensive simulations as well as a lab prototype that measures hyperspectral video at a spatial resolution of $600 \times 900$600×900 pixels, at a spectral resolution of 10 nm over visible wavebands, and achieving a frame rate at 18fps.