Image blurring and spectral drift in imaging spectrometer system with an acousto-optic tunable filter and its application in UAV remote sensing

ABSTRACT

In the design and research of an unmanned aerial vehicle-borne hyperspectral imager with an acousto-optic tunable filter (AOTF), the depth of the field range of the imaging objective lens is fixed, the spectral range of 400–1000nm is wide, and the AOTF crystal has different deflection angles for diffracted light of different wavelengths. These features all cause problems such as image blurring and spectral drifts. Therefore, we propose a solution using a tunable zoom lens and multi-modal spectrum registration to solve these problems. We also propose an improved image definition evaluation function using the zoom lens to obtain clear horizontal lines and blurred vertical lines and, thereby, hope to overcome image blurring in an AOTF spectrometer. The zoom parameters corresponding to the clear image in each spectral segment of the AOTF spectrometer can be determined rapidly and accurately. However, it is difficult to establish a mathematical model of the drift, using wavelength as a variable, to compensate the drift due to the clear image of each spectrum obtained using the zoom lens. The calibration method completes the registration of the spectral data cube composed of clear images, solving the problem of spectral band drift. Moreover, it has been verified through UAV-borne hyperspectral imaging that image blurring and spectral drift of the AOTF imaging spectrometer were significantly reduced, providing opportunities for the application and research of AOTF-based hyperspectral imagers in more fields, such as remote sensing.

Key policy highlights

• A new method using a tunable zoom lens to solve the imaging blur of an AOTF spectrometer with wide spectral band is proposed, which is different from previous methods.

• Using the characteristics of a clear horizontal line and a blurred vertical line of an AOTF spectrometer, an improved image definition evaluation function is proposed to determine zoom parameters quickly and accurately.

• The multi-modal registration method realizes the registration of a spectral data cube, which solves the problem of spectral segment drift of an AOTF spectrometer and that of spectral image registration in UAV-borne remote sensing.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Additional information

Funding

This research was funded by a Class A plan from a major strategic pilot project of the Chinese Academy of Sciences: XDA23040101; National Natural Science Foundation of China: 61872286 and 62272376; Key R&D Program of Shaanxi Province of China :2020ZDLGY04-05 and S2021-YF-YBSF-0094; Shaanxi Key Laboratory of Deep Space Exploration Intelligent Information Technology under Grants No. 2021SYS-04; National Key R&D Program of China: 2017YFC1403700; and “Light of the west” project of Chinese Academy of Sciences: XAB2017B25.