Large-scale liftoff distance satellite-borne SAR image mosaicking method

Abstract

The invention provides a large-scale liftoff distance satellite-borne SAR image mosaicking method, and relates to the field of satellite SAR (synthetic aperture radar) image mosaicking. The method comprises the following steps of: carrying out necessary preprocessing on an original image; extracting geographic location information of the preprocessed image; carrying out correlated correction on the image by taking the geographic location information as a priori knowledge so as to obtain mosaicking error information; compensating an image mosaicking error by utilizing the mosaicking error information; after the mosaicking error compensation, carrying out uniform color processing on the input SAR image in a search updating manner by utilizing a Wallis filter; and finally generate a mosaickedimage. According to the method, a cross-correlation method or zero crossing point-based binary matching statistical method is adapted according to different terrains, so that selectable schemes are provided for the determination of matching offsets; and a search updating strategy is provided, so that a uniform color processing effect at multiple overlapping areas in multiple directions is ensured, and texture details in the images can be well protected.

Description

Technical field [0001] The invention relates to the field of satellite SAR (Synthetic Aperture Radar) image mosaic, in particular to a large-scale ground-range satellite SAR image mosaic method. Background technique [0002] Spaceborne Synthetic Aperture Radar (SAR) has become an important tool in the field of surveying and mapping and earth sciences due to its large area and all-weather, day and night imaging capabilities. The mosaic of multiple SAR images from the same and adjacent imaging tracks is particularly useful for monitoring and analyzing the spatial and temporal changes of the global process. Spaceborne SAR mosaic products can be widely used in fields such as land use, land cover change, mapping, coastline, desertification, wetland and glacier monitoring. The key to ground-range satellite-borne SAR mosaic is to eliminate the geometric structure dislocation and radiation difference between mosaic images, and is not limited by the large-capacity memory. [0003] At pres...

AI Technical Summary

Problems solved by technology

These methods usually need to register overlapping image data using visually positioned homonymous points or visual features extracted by some algorithm, and the entire mosaic process is laborious and time-consuming; It can only realize the gradual transition of overlapping areas in one direction, and it is difficult to eliminate the problem of chromatic aberration caused by overlapping areas in multiple directions; in addition, some methods require higher memory capacity of the computer

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