The automatic registration of image pairs composed of optical and synthetic aperture radar (SAR) images is a highly challenging task because of the inherently different physical, statistical, and textural properties of the input data. Information-theoretic measures capable of comparing local intensity distributions are often used for multisensor optical-SAR registration. Moreover, the growing availability of such heterogeneous data from current space missions require multisensor registration methods able to run on large-scale datasets with acceptable computation times. In this paper, a novel method is proposed combining information-theoretic area-based registration with a sequential image tiling strategy. Experiments with optical-SAR data collected by a variety of sensors (Sentinel, Landsat, ERS, etc.) suggest both qualitatively and quantitatively the effectiveness of the proposed strategy in achieving accurate registration with low computational cost.

A Tiling-Based Strategy for Large-Scale Multisensor Optical-Sar Image Registration

Solarna D.;Maggiolo L.;Moser G.;Serpico S. B.
2022-01-01

Abstract

The automatic registration of image pairs composed of optical and synthetic aperture radar (SAR) images is a highly challenging task because of the inherently different physical, statistical, and textural properties of the input data. Information-theoretic measures capable of comparing local intensity distributions are often used for multisensor optical-SAR registration. Moreover, the growing availability of such heterogeneous data from current space missions require multisensor registration methods able to run on large-scale datasets with acceptable computation times. In this paper, a novel method is proposed combining information-theoretic area-based registration with a sequential image tiling strategy. Experiments with optical-SAR data collected by a variety of sensors (Sentinel, Landsat, ERS, etc.) suggest both qualitatively and quantitatively the effectiveness of the proposed strategy in achieving accurate registration with low computational cost.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1102955
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