SAR image compression method based on robust tensor decomposition

Abstract

The invention discloses an SAR image compression method based on robust tensor decomposition, and the method comprises the following steps: converting an original multi-channel SAR image into a tensor; performing mode-n expansion on the tensor to obtain a mode-n matrix, and verifying sparse distribution characteristics of SAR multi-channel image tensor decomposition singular values; setting a singular value threshold value, retaining singular values exceeding the threshold value, performing zero setting on the residual singular values, and performing singular value truncation processing; obtaining approximate tensor representation based on singular value truncation and serving as an initial iteration value of multichannel SAR image compression; calculating robust tensor decomposition based on an augmented Lagrangian multiplier method, and performing dimensionality reduction on the singular value matrix; and performing tensor reconstruction by using the data obtained by dimension reduction to obtain a final multi-channel SAR image compression result. According to the method, the SAR multi-channel image is converted into a tensor form, and the robust tensor decomposition technology is utilized to carry out high-dimensional principal component sparse representation on the image, so that remote sensing SAR image compression is realized, and the influence of an outlier on the image compression effect is effectively inhibited.

Description

technical field [0001] The invention relates to the technical field of radar image processing, in particular to a SAR image compression method based on robust tensor decomposition. Background technique [0002] With the development of remote sensing technology, remote sensing images play an increasingly important role in social life. Among them, the Synthetic Aperture Radar (SAR) that has emerged in recent years has the characteristics of high resolution. The new radar microwave imaging technology is favored. Due to its coherent imaging characteristics, the SAR image obtained by synthetic aperture radar contains rich multiple information such as phase and amplitude. SAR images are usually large in size and have a high amount of data, which poses certain difficulties for storage and transmission. The prerequisite for making full use of SAR image information resources is to consider the characteristics of SAR images, and to study its efficient compression methods has importa...

AI Technical Summary

Problems solved by technology

Considering the unique characteristics of these SAR images, the superiority of image compression algorithms such as traditional JPEG and JPEG2000 cannot be effective for SAR data images

Because the traditional compression method does not take into account the spatial structure of high-dimensional data, it often just vectorizes the image data and then performs the corresponding compression operation, so the traditional method completely destroys the structural characteristics of high-dimensional data and is not suitable for SAR image processing

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