Spline warp model for registering pushbroom multispectral imagery

Suhail S. Saquib; Matthew D. Egan; Christopher M. Gittins

doi:10.1117/12.2266796

1 May 2017 Spline warp model for registering pushbroom multispectral imagery

Suhail S. Saquib, Matthew D. Egan, Christopher M. Gittins

Proceedings Volume 10204, Long-Range Imaging II; 1020402 (2017) https://doi.org/10.1117/12.2266796
Event: SPIE Defense + Security, 2017, Anaheim, CA, United States

Abstract

We describe an algorithm for registering spectral images acquired by a pushbroom multispectral scanner operating on an airborne or spaceborne platform subject to uncontrolled motion, i.e., variable time-dependent attitude (pitch, roll, and yaw) and platform position. In contrast to imagery collected during straight and level flight, uncontrolled platform motion causes each band to be warped with respect to the others. The warped bands cannot be simply registered using a rigid transformation but instead require a space-varying de-warping transformation. However, determination of this de-warping transformation from image data remains a challenging problem. In this paper, we formulate a powerful yet efficient model for the warp that takes into account both the detector array geometry and the imaging geometry. The physically-based geometric constraints incorporated into the model enable it to distinguish effectively between image-to-image warp due to uncontrolled variations in the sensor line-of-sight and band-to-band variations in image content and measurement noise. Results show that the model is capable of recovering the true warp in areas where there is little or no correlation in spatial content between the bands. For the test cases studied, the spline-warp model is able to reduce the registration error in the local warp determined from data using image correlation techniques by more than an order of magnitude.

Citation Download Citation

Suhail S. Saquib, Matthew D. Egan, and Christopher M. Gittins "Spline warp model for registering pushbroom multispectral imagery", Proc. SPIE 10204, Long-Range Imaging II, 1020402 (1 May 2017); https://doi.org/10.1117/12.2266796

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KEYWORDS

Data modeling

Sensors

Distortion

Motion models

Multispectral imaging

Staring arrays

Image registration

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