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Multi-scale spectral clustering and decision fusion-based oil spillage detection method for synthetic aperture radar (SAR) images

A technology of decision-level fusion and detection method, applied in the field of SAR image oil spill detection, can solve the problems of serious coherent speckle noise and unreliable detection results, and achieve the effect of fast oil spill detection

Active Publication Date: 2013-08-07
HOHAI UNIV
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Problems solved by technology

Since there are many non-oil spill areas and oil spill areas in SAR image oil spill detection, which have similar backscattering characteristics, and the coherent speckle noise is serious, the detection results at a single scale are not reliable

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Embodiment Construction

[0020] Below in conjunction with specific embodiment, further illustrate the present invention, should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various equivalent forms of the present invention All modifications fall within the scope defined by the appended claims of the present application.

[0021] Such as figure 1 As shown, the SAR image oil spill detection method based on multi-scale spectral clustering and decision-level fusion, firstly, establishes the SAR image multi-scale object-level spectral clustering segmentation method based on wavelet transform, and extracts oil spills or suspected oil spills at different scales. The oil spill area; secondly, for the above image segmentation results, the neural network oil spill recognition method combined with multiple indicators is used ...

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Abstract

The invention discloses a multi-scale spectral clustering and decision fusion-based oil spillage detection method for synthetic aperture radar (SAR) images. The oil spillage detection method comprises the following steps of firstly, establishing a multi-scale object-level spectral clustering segmentation method for the SAR images based on wavelet transformation, and respectively extracting an oil spillage area or a suspected oil spillage area under different scales; secondly, identifying image segmentation results by utilizing a neural network oil spillage based on the combination of multiple indexes on a single scale, establishing a multi-scale decision fusion strategy, and fusing detection results of the single scale to complete detection and form a unified detection framework; and performing the performance evaluation of a new oil spillage identification method by taking the main performance index in an identification process as the basis. According to the multi-scale spectral clustering and decision fusion-based oil spillage detection method for the SAR images disclosed by the invention, spectral clustering-based segmentation and the identification of the oil spillage area and the suspected oil spillage area of the sea are performed under different scales by replacing elements with objects to serve basic units, and by a multi-scale decision oil spillage detection fusion algorithm, oil spillage detection is more rapid and accurate.

Description

technical field [0001] The invention relates to a SAR image oil spill detection method based on multi-scale spectral clustering and decision-level fusion, and belongs to the technical field of image detection. Background technique [0002] In recent years, with the rapid development of marine transportation and offshore oil exploitation, oil spill accidents are common, causing serious pollution to the marine environment. The use of satellite remote sensing technology can monitor marine oil spill pollution in a timely, accurate and comprehensive manner, and actively take oil spill removal and preventive measures to protect the marine environment. [0003] SAR image detection of oil slicks on the sea surface has the following salient features: rich image information, clear outline of the observed target, good contrast, can show more details of the target, can accurately determine the size of the target area, and can better distinguish the characteristics of adjacent targets. ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
Inventor 朱立琴高成
Owner HOHAI UNIV
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