Author
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ERIVES, HECTOR - SCI SYS & APP INC, MD |
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Fitzgerald, Glenn |
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Submitted to: International Society for Optical Engineering
Publication Type: Proceedings Publication Acceptance Date: 7/6/2004 Publication Date: 10/15/2004 Citation: Erives, H., Fitzgerald, G.J. 2004. Automated registration of hyperspectral images. In Wel Gao and David R. Shaw (eds.) Proceedings of SPIE-The International Society for Optial Engineering, Remote Sensing and Modeling of Ecosystems for Sustainability, August 2-4, 2004, Denver, Colorado. 5544:328-335. Interpretive Summary: Hyperspectral remote sensing allows the acquisition of dozens to hundreds of images of a single scene at discrete wavelengths of light in the visible and near-infrared portions of the spectrum. One type of hyperspectral imager can acquire images sequentially at numerous spectral wavelengths. Since it takes time to step through the images, they will be offset when the camera package is mounted on a movig aerial platform, such as a helicopter. This makes analysis nearly impossible. To co-register these images, a method called Phase Correlation is presented which allows the images to be aligned. This method accounts for differences in illumination between successive images, noise, blurring due to vibration and aircraft movement, and image vignetting or drop-off in illumination across the image caused by non-uniformity of the lens and filters. This method was tested on images acquired by the Portable Hyperspectral Tunable Imaging System (PHyTIS)over USDA-ARS cotton research fields near Phoenix, AZ. Results showed that the method was successful at co-registering the images to within plus or minus one pixel across the entire set of images. Software methods to correct raw imagery are critical for hyperspectral remote sensing to be useful to scientists or managers of agricultural or natural resources. Technical Abstract: Hyperspectral images of the Earth's surface are increasingly being acquired from aerial platforms. The dozens or hundreds of bands acquired by a typical hyperspectral sensor are acquired either through a scanning process or by collecting a sequence of images at varying wavelengths. This latter methods has the advantage of acquiring coherent images of a scene at different wavelengths. However, it takes time to collect these images and some form of co-registration is required to build coherent image cubes. In this paper, we present a method to register many bands acquired sequentially at different wavelengths from a helicopter. We discuss the application of the Phase Correlation (PC) Method to recover scaling, rotation, and translation from an airborne hyperspectral imaging system, dubbed PHyTIS. This approach is well suited for remotely sensed images acquired from a moving platform, which induces image registration erros due to along and across track movement. We were able to register images to within ± 1 pixels across entire image cubes from the PHyTIS hyperspectral imaging system, which was developed for precision farming applicationsHyperspectral images of the Earth's surface are increasingly being acquired from aerial platforms. The dozens or hundreds of bands acquired by a typical hyperspectral sensor are acquired either through a scanning process or by collecting a sequence of images at varying wavelengths. This latter method has the advantage of acquiring coherent images of a scene at each wavelength but since it takes time to collect these images, some form of co-registration is required to build coherent image cubes. This paper discusses the application of the Phase Correlation (PC) Method to recover scaling, rotation, and translation from a hyperspectral imaging system. This approach is well suited for remotely sensed images acquired from a platform that is moving (along and across track). We were able to register images to within ± 1 pixels across entire image cubes obtained from a hyperspectral imaging system suitable for precision farming tasks. |
