Robust Phase-Correlation Based Registration of Airborne Videos Using Motion Estimation
نویسندگان
چکیده
This paper presents an algorithm for near-real time registration of airborne video sequences with reference images from a different sensor type. Phase-correlation using Fourier-Melin Invariant (FMI) descriptors allow to retrieve the rigid transformation parameters in a fast and non-iterative way. The robustness to multi-sources images is obtained by an enhanced image representation based on the gradient norm and by the extrapolation of registration parameters by motion estimation between frames. A phase-correlation score, indicator of the registration quality, is introduced to regulate between frame-toreference image registration and extrapolation from previous frames only. Our Robust Phase-Correlation based registration algorithm using Motion Estimation (RPCME) is compared with a Mutual Information (MI) algorithm for the registration of two different panchromatic airborne videos with Geoeye reference images. The RPCME algorithm registered most of the frames accurately, retrieving much better orientation than MI. It shows robustness and good accuracy to multisource images with the advantage of being a direct (non-iterative) method. F. de Morsier (&) J.-P. Thiran École Polytechnique Fédérale de Lausanne, LTS 5, Lausanne, Switzerland e-mail: [email protected] M. Borgeaud European Space Agency, ESRIN, Frascati, Italy C. Küchler A. Vogel RUAG Schweiz AG, Emmen, Switzerland V. Gass Swiss Space Center, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland J. M. Krisp et al. (eds.), Earth Observation of Global Changes (EOGC), Lecture Notes in Geoinformation and Cartography, DOI: 10.1007/978-3-642-32714-8_3, Springer-Verlag Berlin Heidelberg 2013 37
منابع مشابه
Robust Phase Correlation Based Feature Matchinig for Image Co-registration and Dem Generation
This paper presents a robust phase correlation based sub-pixel feature matching technique and its application in motion flow estimation, pixel-to-pixel image-co-registration and DEM generation. We propose to use a phase fringe filter and a highly robust technique in the direct Fourier-based phase correlation algorithm for translational shift estimation in sub-pixel accuracy. Noting the problem ...
متن کاملEvaluation and Practical Issues of Subpixel Image Registration Using Phase Correlation Methods
In this study we first propose and compare two frequencydomain motion estimation methods using phase correlation principle. Then, we focus on the particular case of subpixel translational movements, we evaluate the accuracy of these two registration methods and we give some practical hints for their implementation. Finally, we compare the performances of these methods for both an ideal theoreti...
متن کاملImprovement of Biomass Estimation in Forest Areas based on Polarimetric Parameters Optimization of SETHI airborne Data using Particle Swarm Optimization Method
Estimation of forest biomass has received much attention in recent decades. Airborne and spaceborne (SAR) have a great potential to quantify biomass and structural diversity because of its penetration capability. Polarizations are important elements in SAR systems due to sensitivity of them to backscattering mechanisms and can be useful to estimate biomass. Full Polarimetric Synthetic Aperture ...
متن کاملRobust Phase Correlation based Motion Estimation and Its Applications
This paper presents a robust phase correlation technique and a compound phase correlation method for reliable sub-pixel image feature matching and motion estimation. A phase fringe filter and a highly robust estimator QMDPE are used to improve the fitting accuracy of the phase difference plane in Fourier domain. A compound phase correlation method is proposed to identify and decompose the multi...
متن کاملUnsupervised Camera Motion Estimation and Moving Object Detection in Videos
In this article, we consider the robust estimation of a location parameter using Mestimators. We propose here to couple this estimation with the robust scale estimate proposed in [Dahyot and Wilson, 2006]. The resulting procedure is then completely unsupervised. It is applied to camera motion estimation and moving object detection in videos. Experimental results on different video materials sho...
متن کامل