Synthetic aperture radar image modeling method and synthetic aperture radar image modeling device

Abstract

The invention discloses a synthetic aperture radar image modeling method and a synthetic aperture radar image modeling device. The synthetic aperture radar image modeling method comprises the steps of a first step, creating a gray scale histogram Y; a second step, creating a generalized gamma mixture model; and a third step, based on an HECM-MML-GgammMM algorithm, estimating the mixed weight value of the generalized gamma mixture model, the parameter of each generalized gamma component and an optimal number of the mixture model components, thereby determining the constructed generalized gamma mixture model and finishing image modeling. The synthetic aperture radar image modeling method and the synthetic aperture radar image modeling device can be widely applied on accurate modeling of the SAR image with single-peak or multi-peak distribution characteristic on amplitude and strength and same-texture or heterogeneous-texture characteristic. The parameter has a closed expression form, and furthermore easy realization and high computing efficiency are realized. The synthetic aperture radar image modeling method and the synthetic aperture radar image modeling device have advantages of keeping details in the image, reducing information loss and effectively acquiring image classification result.

Description

technical field [0001] The present invention relates to the technical field of digital image processing, in particular to a synthetic aperture radar image modeling method and device. Background technique [0002] As an important means of earth observation technology, remote sensing platforms (airborne or spaceborne) equipped with Synthetic Aperture Radar (SAR) sensors have the advantages of working in all-weather, all-time, and all-terrain conditions. It has a wide range of applications in detection, ocean forecasting, and disaster monitoring. Today, the rapid development of SAR technology has also greatly expanded its application range. A new generation of high-resolution SAR systems mounted on satellites and aircraft can obtain richer image information than before. However, this also poses new challenges to the interpretation of SAR images, that is, accurate statistical modeling and image classification for SAR image data containing different ground object information an...

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Problems solved by technology

This improves the accuracy of the dictionary-based method to some extent, but its flexibility and computational efficiency are still constrained

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