Arid
DOI10.1117/12.2001537
Parallel algorithms for fast subpixel detection in hyperspectral imagery
Wong, Chung M.; Shepanski, John; Sandor-Leahy, Stephanie
通讯作者Sandor-Leahy, Stephanie
会议名称Conference on Image Processing - Algorithms and Systems XI
会议日期FEB 04-06, 2013
会议地点Burlingame, CA
英文摘要

We present parallel algorithms for fast subpixel detection of targets in hyperspectral imagery produced by our Hyperspectral Airborne Tactical Instrument (HATI-2500). The HATI-2500 hyperspectral imaging system has a blue-enhanced visible-near-IR (VNIR) and a full short-wave IR (SWIR) range response from 400 to 2500 nm. It has an industry-leading spectral resolution that ranges from 6 nm down to 1.5 nm in the VNIR region. The parallel detection algorithm selected for processing the hyperspectral data cubes is based on the adaptive coherence/cosine estimator (ACE). The ACE detector is a robust detector that is built upon the theory of generalized likelihood ratio testing (GLRT) in implementing the matched subspace detector to unknown parameters such as the noise covariance matrix. Subspace detectors involve projection transformations whose matrices can be efficiently manipulated through multithreaded massively parallel processors on modern graphics processing units (GPU). The GPU kernels developed in this work are based on the CUDA computing architecture. We constrain the detection problem to a model with known target spectral features and unstructured background. The processing includes the following steps: 1) scale and offset applied to convert the data from digital numbers to radiance values, 2) update the background inverse covariance estimate in a line-by-line manner, and 3) apply the ACE detector for each pixel for binary hypothesis testing. As expected, the algorithm is extremely effective for homogeneous background, such as open desert areas; and less effective in mixed spectral regions, such as those over urban areas. The processing rate is shown to be faster than the maximum frame rate of the camera (100 Hz) with a comfortable margin.


英文关键词Hyperspectral imaging remote sensing real-time processing parallel computing
来源出版物IMAGE PROCESSING: ALGORITHMS AND SYSTEMS XI
ISSN0277-786X
出版年2013
卷号8655
EISBN978-0-8194-9428-3
出版者SPIE-INT SOC OPTICAL ENGINEERING
类型Proceedings Paper
语种英语
国家USA
收录类别CPCI-S
WOS记录号WOS:000320305600022
WOS类目Optics ; Imaging Science & Photographic Technology
WOS研究方向Optics ; Imaging Science & Photographic Technology
资源类型会议论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/301997
作者单位Northrop Grumman Aerosp Syst, Redondo Beach, CA 90278 USA
推荐引用方式
GB/T 7714
Wong, Chung M.,Shepanski, John,Sandor-Leahy, Stephanie. Parallel algorithms for fast subpixel detection in hyperspectral imagery[C]:SPIE-INT SOC OPTICAL ENGINEERING,2013.
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