A computational approach to hyperspectral imaging for long-range target identification
A computational approach to hyperspectral imaging for long-range target identification
复制标题
用于远程目标识别的高光谱成像计算方法
DOI：
10.1117/12.2305306
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Tanner J
中科院分区：
文献类型：
--
作者：
Tanner J
对于远距离瞄准，与用于机载操作的紧凑型成像传感器相关联的有限焦距和孔径尺寸限制了空间分辨率和图像亮度。这对目标的识别和跟踪构成了严重挑战。导出目标形状和跟踪场景中的运动的算法需要解析的图像，并使用像素对比度来区分目标图像和背景。这是有限的使用时，实际部署需要使用紧凑的成像系统，必然有限的空间resolutions.To解决这个问题，我们考虑了一个二维马赛克滤波器采样方案，以获得一个不完整的多光谱数据立方体上的单帧读出从焦平面阵列。具体来说，稀疏数据立方体包含4 × 4空间单元和16个波段，每个波段对每个单元采样一次;这对应于数据立方体的1/16欠采样。完整的多光谱图像，然后使用压缩感知protocols.Results计算得到的高光谱数据集AVIRIS和斯坦福大学（SCIEN）的结果，演示图像重建使用16个波段的可见光和近红外。马赛克滤波器的功能是通过根据理论马赛克滤波器的设计对完整数据集进行采样来模仿的。这使我们能够研究不同的采样策略，特别是，随机和常规采样之间的直接比较。我们的研究结果表明，重建误差强烈依赖于测试图像中的颜色内容和采样策略，并且可以实现接近原始图像的空间分辨率的非常好的重建。我们的研究结果可以应用到MWIR和LWIR，其中较低的光谱分辨率意味着较少数量的波段可能足以用于识别和跟踪。该概念还可以扩展到具有合适的偏振滤波器掩模的偏振成像，以提供双模偏振多光谱成像能力。本文件概述了技术方法和一般结论。
For long range targeting, the limited focal length and aperture size associated with compact imaging sensors for airborne operation limit both the spatial resolution and the image brightness. This presents a serious challenge to the identification and tracking of targets. Algorithms that derive target shape and track movement through a scene require a resolved image and use pixel contrast to discriminate the target image from the background. This is of limited use when practical deployment demands the use of compact imaging systems with necessarily limited spatial resolution.To address this we consider a 2D mosaic filters sampling scheme to acquire an incomplete multispectral data cube on a single frame readout from a focal plane array. Specifically, the sparse data cube contains 4 x 4 spatial cells and 16 wavebands with each waveband sampled once per cell; this corresponds to a 1/16 undersampling of the data cube. Complete multispectral images are then computed using compressed sensing protocols.Results obtained using hyperspectral datasets from AVIRIS and Stanford University (SCIEN) are presented to demonstrate image reconstruction using 16 wavebands in the visible and near infrared. The function of the mosaic filter is mimicked by sampling the full dataset according to the design of a theoretical mosaic filter. This allows us to investigate different sampling strategies and, in particular, make a direct comparison between random and regular sampling. Our results show that the reconstruction error is strongly dependent on both the colour content and the sampling strategy in the test images, and that very good reconstruction can be achieved approaching the spatial resolution of the original image. Our results can be applied to both the MWIR and LWIR where the lower spectral resolution means that a smaller number of wavebands is likely to be sufficient for identification and tracking. The concept can also be extended to polarimetric imaging with a suitable polarimetric filter mask to provide a dual-mode polarimetric-multispectral imaging capability. This paper presents an overview of the technical approach and the general conclusions.
DOI：
10.1109/jstsp.2010.2042411
发表时间：
2010-04-01
影响因子：
7.5
作者：
Blumensath, Thomas;Davies, Mike E.
通讯作者：
Davies, Mike E.