SAR image target recognition method based on wavelet threshold denoising combined with convolutional neural network

A technology of convolutional neural network and wavelet threshold, which is applied in target recognition, image processing, synthetic aperture radar image target recognition, and feature extraction, can solve the problem of not effectively removing image speckle noise and retaining target outline information, etc. The effect of target recognition effect

Inactive Publication Date: 2018-11-27
ZHEJIANG UNIV OF TECH
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Problems solved by technology

[0005] In order to overcome the problem that the existing SAR image target recognition method does not effectively remove image speckle noise and retain target contour information, and requires manual design, feature selection and classifier for target recognition, the present invention proposes a wavelet thres

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  • SAR image target recognition method based on wavelet threshold denoising combined with convolutional neural network
  • SAR image target recognition method based on wavelet threshold denoising combined with convolutional neural network
  • SAR image target recognition method based on wavelet threshold denoising combined with convolutional neural network

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[0040] Below in conjunction with accompanying drawing and embodiment the present invention will be further described

[0041] In this embodiment, the MSTAR data set is used as the experimental data set. The MSTAR data set is a SAR image data set published by the MSTAR program for scientific research, and it is a data set commonly used to scientifically evaluate the performance of SAR automatic target recognition systems. The MSTAR data set includes a total of 10 types of ground tactical targets, namely BTR70, D7, ZSU_234, BRDM_2, T72, BTR_60, 2S1, ZIL131, T62 and BMP2. Table 1 shows the training and testing examples of 10 types of targets.

[0042]

[0043] Table 1

[0044] refer to Figure 1 to Figure 10 , a wavelet threshold noise reduction combined with a convolutional neural network SAR image target recognition method, comprising the following steps:

[0045] Step 1, wavelet decomposition of SAR target image

[0046] Adjust the training samples uniformly to a magni...

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Abstract

A SAR image target recognition method based on wavelet threshold denoising combined with a convolutional neural network includes the following steps: a step 1, performing 2-layer 2D wavelet decomposition on a SAR target image; a step 2, using a Bayesian estimated threshold to quantize a high frequency coefficient after wavelet decomposition; a step 3, performing wavelet image reconstruction on a low-frequency coefficients after wavelet decomposition and the high-frequency coefficient after threshold quantization; and a step 4, using the convolutional neural network to automatically learn multi-layer features from the reconstructed SAR target image to characterize the image, and using a Softmax classifier to recognize a target type. The method can overcome the influence of speckle noise oncontour details of the image and reduce the dependence on artificial design, selection features and classifiers, and improve the performance of SAR image target recognition.

Description

technical field [0001] The invention relates to the fields of image processing, feature extraction, target recognition and the like, and in particular to the field of synthetic aperture radar image target recognition. Background technique [0002] Synthetic Aperture Radar (SAR) has the advantages of all-weather, all-day and long-distance detection, and can detect long-distance targets under any weather conditions and at night. At the same time, SAR has high resolution in range and azimuth, can obtain two-dimensional high-resolution radar images in the irradiation area, provide detailed ground detection data, and is widely used in military and civilian fields. Among them, one of the main applications of SAR in civilian and military applications is to discover and identify military targets, such as aircraft, tanks, airports and aprons, armored vehicles, missile launchers, various vehicles, ships, etc. [0003] SAR image target recognition refers to the technology of using SAR...

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Application Information

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IPC IPC(8): G06K9/62G06K9/40G06N3/04
CPCG06V10/30G06N3/045G06F18/2415
Inventor 宦若虹杨鹏鲍晟霖葛罗棋
Owner ZHEJIANG UNIV OF TECH
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