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Biased field level set-based sonar image segmentation method

An image segmentation and level set technology, applied in image analysis, image enhancement, image data processing, etc., can solve problems such as inapplicability and complex algorithms, achieve good segmentation results, do not increase the amount of calculation, and resist noise interference

Active Publication Date: 2018-08-28
HARBIN ENG UNIV
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Problems solved by technology

This method utilizes the Markov segmentation model, but the overall algorithm is relatively complex and not suitable for operation in the actual marine environment

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  • Biased field level set-based sonar image segmentation method
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Embodiment Construction

[0050] Further describe the present invention below in conjunction with accompanying drawing:

[0051] Such as figure 1 , a sonar image segmentation method based on offset field level sets, comprising the following steps:

[0052] Step (1): If figure 2 , performing non-subsampling contourlet transformation on the source image, performing multi-scale decomposition of the first-level and second-level images respectively, to obtain low-frequency sub-band images, including the first low-frequency image and the second low-frequency image;

[0053] Step (2): According to the low-frequency sub-band image, combined with the Markov four-neighborhood model, estimate the parameters of the Markov four-neighborhood model:

[0054] in the image domain Assuming that any point x pixel value I(x) is a random variable, I(x)=I x The probability P(I(x)=I x ) is expressed as the conditional probability P(I x |Ω). A certain neighborhood of pixel x is denoted as η x , when the probability P(...

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Abstract

The invention discloses a biased field level set-based sonar image segmentation method and belongs to the digital image processing field. The method includes the following steps that: multi-scale decomposition is performed on a source image, so that a low-frequency sub-band image can be obtained; Markov four-neighbor model parameters are estimated through a Markov four-neighbor model according tothe low-frequency sub-band image; the Markov four-neighbor model parameters are re-substituted into the low-frequency sub-band image, so that a local texture image can be obtained; and a three-phase model biased field level set theory is derived according to an original biased field level set theory; and the local texture image is substituted into the source image, and the energy function of an improved biased field level set model is constructed, the energy function of the improved biased field level set model is minimized, so that a contour can be driven to converge to an edge region; and asegmentation result is outputted. With the biased field level set-based sonar image segmentation method of the invention adopted, the noise interference of a sonar image can be effectively resisted, three types of regions in the sonar image can be obtained through accurate segmentation with a calculation amount not increased.

Description

technical field [0001] The invention belongs to the field of digital image processing, in particular to a sonar image segmentation method based on an offset field level set. Background technique [0002] As the development of marine resources has attracted more and more attention from all countries in the world, the exploration, search and investigation of underwater resources are also in full swing. Due to the complexity of the underwater environment, sonar is a The most effective sensor currently used in underwater detection. Since the sonar system was born in the late 1950s, sonar equipment used in the military field is mainly used for obstacle avoidance, and the discovery, tracking and identification of some military targets; in recent years, with the development of marine development activities , the application of sonar equipment is not limited to military purposes, and has even been applied to commercial and civilian fields, such as seabed resource development, oil e...

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Application Information

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IPC IPC(8): G06T7/11
CPCG06T7/11G06T2207/10132G06T2207/20116
Inventor 卞红雨张健张志刚黄靖伟王子麒
Owner HARBIN ENG UNIV