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Automatic detection method for airport of large-size space-borne SAR image

An automatic detection, large-scale technology, applied in image analysis, image data processing, measurement devices, etc., can solve the problems of poor image quality, false detection, strong speckle noise in SAR images, and achieve fast recognition speed and good recognition quality. , the effect of high recognition accuracy

Inactive Publication Date: 2010-12-22
TONGJI UNIV
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AI Technical Summary

Problems solved by technology

For the automatic detection of airports in large-scale spaceborne SAR images, there are relatively few researches at home and abroad, and most of the existing research results rely on the pre-given location information of airport interest areas.
The main difficulties in the automatic detection of airports in large-scale spaceborne SAR images are: (1) the coherent speckle noise in SAR images is strong, and the image quality is poor; (2) the background of large-scale spaceborne SAR images is complex, and there are targets similar to airports , it is easy to cause false detection

Method used

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  • Automatic detection method for airport of large-size space-borne SAR image
  • Automatic detection method for airport of large-size space-borne SAR image
  • Automatic detection method for airport of large-size space-borne SAR image

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Embodiment

[0051] In this embodiment, airport detection is performed on a large-scale spaceborne SAR image, and there is an airport target in the image. The image as figure 1 shown. The image size is 4200×4700. figure 2 The image segmentation results are shown, which are divided into 5 types of targets (the gray scale of the segmentation results is 5 levels). image 3 Extract results for interest targets. In this example, a total of 1570 interest targets are extracted. After SVM classification, 7 objects were identified as airports. Figure 4 , Figure 5 The minimum area bounding rectangle and projected histogram of the airport target are shown, respectively. Figure 6 , Figure 7 The minimum area bounding rectangle and projected histogram of a non-airport object are shown, respectively. Figure 8 The final detection results obtained by parallel runway detection are shown. Figure 9 The final detected airport location 1 is shown.

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Abstract

The invention relates to an automatic detection method for an airport of a large-size space-borne SAR image, which comprises the following steps of: A, performing SAR image segmentation based on a maximum posterior probability criterion; B, extracting interesting targets according to the pixel intensity and the area of the airport; C, extracting dimensions and rotary invariable parameters of the interesting targets; D, training a support vector machine classifier according to the dimensions and the rotary invariable parameters of the interesting targets, and classifying the interesting targets to obtain an initial detection result; and E, performing parallel runway detection on the initial detection result, and retaining the targets with parallel runways as final detection results. Compared with the prior art, the method has the advantages of high identification speed, good identification quality and high identification accuracy rate.

Description

technical field [0001] The invention relates to SAR image target detection, in particular to an airport automatic detection method for large-scale spaceborne SAR images. Background technique [0002] SAR has all-day and all-weather imaging capabilities, and has a certain penetration, and has a very wide range of applications in national economic construction and military affairs. As an important traffic and military target, the automatic detection of airports has always been an important research content in SAR image interpretation, and its methods mainly involve image processing and pattern recognition related theories. For large-scale spaceborne SAR images (approximately 5000×5000 pixels), the automatic detection of airport targets is very difficult due to its complex background and strong coherent speckle noise. At present, there have been many studies on the automatic detection of airports in large-scale optical remote sensing images, such as the rapid interpretation of...

Claims

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Application Information

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IPC IPC(8): G01S13/90G06T7/00
Inventor 张绍明林怡陈映鹰
Owner TONGJI UNIV
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