Advantages of the Boresight Effect in Hyperspectral Data Analysis
نویسندگان
چکیده
Dual pushbroom hyperspectral sensors consist of two different instruments (covering different wavelengths) that are usually mounted on the same optical bench. This configuration leads to problems, such as co-registration of pixels and squint of the field of view, known as the boresight effect. Determination of image-orientation parameters is due to the combination of an inertial measurement system (IMU) and global position system (GPS). The different positions of the IMU, the GPS antenna and the imaging sensors cause the orientation and boresight effect. Any small change in the correction of the internal orientation affects the co-registration between images extracted from the two instruments. Correcting the boresight effect is a key and almost automatic task performed by all dual-system users to better analyze the full spectral information of a given pixel. Thus, the boresight effect is considered to be noise in the system and a problem that needs to be corrected prior to any (thematic) data analysis. We propose using the boresight effect, prior to its correction, as a tool to monitor and detect spectral phenomena that can provide additional information not present in the corrected images. The advantage of using this effect was investigated with the AISA-Dual sensor, composed of an EAGLE sensor for the VIS-NIR (VNIR) region (400–970 nm) and HAWK for the SWIR region (980–2,450 nm). During the course of more than six years of operating this sensor, we have found that the boresight effect provides a new capacity to analyze hyperspectral data, reported herein. Accordingly, we generated a protocol to use this effect for three applications: (1) enhancing the shadow effect; (2) generating a 3-D view; and (3) better detecting OPEN ACCESS Remote Sensing 2011, 3 485 spectral/spatial anomalies based on sub-pixel edge detection. This paper provides examples of these applications and suggests possible uses from an airborne platform.
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ورودعنوان ژورنال:
- Remote Sensing
دوره 3 شماره
صفحات -
تاریخ انتشار 2011