SAR image target classification method based on NSCT double CNN channels and selective attention mechanism

Abstract

The invention discloses an SAR image target classification method based on NSCT double CNN channels and a selective attention mechanism. The method comprises steps that training sample sets D1 and D2 for target detection and classification are acquired; the D1 and D2 are expanded to acquire sample sets D3 and D4; models M1 and M2 for target detection and classification are respectively trained; significance detection and morphological processing on test images are carried out, connected domain marking is further carried out, target candidate areas corresponding to a connected domain mass center are extracted, translation in multiple surrounding pixel points is carried out, and the target candidate areas are generated; classification determination of the target candidate areas is carried out through utilizing the M1, and accurate positioning of a target is acquired; a final class of the target is determined through voting decision after M2 classification. The method is advantaged in that a non-down-sampling contour wave layer is added, low frequency and high frequency characteristic images are inputted to a double channel CNN to form the NSCT double channel CNN, the selective attention mechanism is applied to SAR image classification, SAR image target detection classification accuracy is improved, and a problem of low target classification accuracy in the prior art is solved.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a synthetic aperture radar SAR (Synthetic Aperture Rader) image target based on NSCT (non-subsampled contourlet) dual CNN channel convolutional neural network (Convolutional Neural Network) and selective attention mechanism Classification method, the invention can be used for target classification and identification of synthetic aperture radar SAR images. Background technique [0002] As an active sensor, the resolution of synthetic aperture radar has nothing to do with the observation distance. At present, SAR has become one of the indispensable means of military reconnaissance and geographic remote sensing. [0003] Target detection and classification of SAR images is an important problem in SAR image processing and interpretation. At present, many of the target detection and classification of SAR images are based on pixel-level processing, and statistica...

AI Technical Summary

Problems solved by technology

Although there are many feature extraction methods, target detection in SAR images is still a challenging problem due to the existence of factors that affect the saliency of images such as noise and shadows in SAR images.

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