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Wavelet reinforcement based compound aperture radar image method for detecting ship object

A technology for synthetic aperture radar and target detection, applied in the field of image processing, can solve problems such as background clutter difficulty and fitting, and achieve the effects of weakening background noise, improving estimability, and enhancing SAR image ship and ship target signals

Inactive Publication Date: 2007-02-28
GRADUATE SCHOOL OF THE CHINESE ACAD OF SCI GSCAS
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Problems solved by technology

[0007] In order to solve the problem that the complex background clutter in the classic SAR image ship target detection algorithm is difficult to accurately fit with the mathematical probability model, the present invention provides a SAR image ship based on Wavelet Multiscale Products (WMP for short). Target Signal Enhancement and Noise Removal Methods

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  • Wavelet reinforcement based compound aperture radar image method for detecting ship object
  • Wavelet reinforcement based compound aperture radar image method for detecting ship object
  • Wavelet reinforcement based compound aperture radar image method for detecting ship object

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Embodiment Construction

[0018] 1. Wavelet multiscale product enhancer

[0019] Analyze the formation mechanism of SAR image speckle noise and the characteristics of wavelet coefficients, the present invention adopts the detector structure diagram of Fig. 3, wherein 6 is the wavelet multi-scale product enhancer module, and it is by analysis low-pass filter, analysis high-pass filter, threshold value Filter, multiplier, integrated low-pass filter, integrated high-pass filter and adder, the present invention uses three-stage wavelet transform to achieve the purpose of enhancing SAR, the detailed structure is shown in Figure 4.

[0020] There are two types of discrete wavelet transform for realizing signals: Decimated Discrete Wavelet Transform (DDWT for short) and Undecimated Discrete Wavelet Transform (UDWT for short). Since UDWT has translation invariance, it can more accurately estimate Signal waveform, the present invention uses UDWT to calculate the wavelet coefficient of the signal. When doing wa...

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Abstract

The invention relates to a SAR picture ship target detecting method, based on wavelet multiple-dimension product enhancement, wherein it is based on the general Synthetic Aperture Radar picture ship target detecting method, which has inaccurate background foreign wave probability distribution and low detecting property, via wavelet multiple-dimension product enhancement method to treat the SAR picture with three-step non-sample wavelet conversion, to treat the high-frequency component with threshold value filter to separate out the low absolute wavelet factor, and product the wavelet factors at different sizes and same position, to obtain high-frequency wavelet factor via multiple-dimension product enhancement; and using said high-frequency component and wavelet converted low-frequency component to rebuild enhanced SAR picture, as the detected picture to be input into dual-factor constant false alarm probability detector, to improve the detecting property.

Description

technical field [0001] The invention relates to a method for detecting a target in the field of image processing, in particular to a method for detecting a ship target in an image of a Synthetic Aperture Radar (SAR) image enhanced by wavelets. Background technique [0002] Early SAR image ship target detection uses a simple threshold method, which is mainly suitable for the situation where the background clutter is simple and the ship target angle reflection signal is strong. With the development of SAR, the constant false alarm probability detection algorithm of Cell Averaging (CA for short), the constant false alarm probability detection algorithm of Ordered Statistics (OS for short) and the median and shape ( Median and Morphological (MEMO for short) filter constant false alarm probability detection algorithm. In order to adapt to the transformation of background clutter, Gaussian probability model, lognormal model, gamma distribution model, Weibull model and K-distribut...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S13/90
Inventor 凃国防陈德元张灿
Owner GRADUATE SCHOOL OF THE CHINESE ACAD OF SCI GSCAS
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