Method for recognizing SAR target based on curvelet transform

Abstract

The invention discloses a method for recognizing an SAR target based on curvelet transform, and relates to the technical field of image processing and target recognition. The invention mainly solves the problems of low recognition rate and large volume of data existing in the prior method for recognizing the SAR target. The implementation process comprises the followings steps of: smoothing medianfiltering; performing nonlinear normalization; performing threshold segmentation after window filtering; extracting low-frequency subband information and the threshold segmentation by the curvelet transform; forming a fine characteristic area by morphological treatment; orderly performing the smooth filtering, the nonlinear normalization, the window filtering and the extraction of the low-frequency subband information of an image by the curvelet transform to form a rough characteristic area; combining the fine characteristic and the rough characteristic as a final target characteristic vectorto train and support a vector classifier; and recognizing the SAR target by the well trained classifier. The method has the advantages of reducing the volume of data and improving the recognition rate, and can be applied to the identification of SAR ground targets.

Description

technical field [0001] The invention belongs to the technical field of image processing and relates to target identification, in particular to a method for identifying SAR targets, which can be used for identifying SAR image targets. Background technique [0002] Synthetic Aperture Radar (SAR, Synthetic Aperture Radar) is an all-weather and all-weather radar system with high resolution and penetrating capability, and has a wide range of applications in battlefield awareness. However, due to the external noise of its imaging mechanism, SAR images cannot be observed and understood as easily as optical images, so they must be identified. [0003] Object recognition is an important link in the process of image processing. The task of target recognition is to correctly identify the target to be recognized through the designed algorithm, but these targets must have certain prior knowledge or training samples to train the classifier, so as to further verify the recognition results...

AI Technical Summary

Problems solved by technology

The disadvantage of this method is that the matching process takes a lot of time, and it is only the most primitive matching similarity principle, resulting in an unsatisfactory template matching recognition rate.

However, this method mainly focuses on the design of an effective classifier. Although it can also extract target features, the extracted target features are not accurate enough, which affects the recognition rate of SAR targets; The frequency domain information of the discrete Fourier transform also leads to the problem of high computational complexity

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