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Image segmentation method based on non-subsampling shearlet transform and vector c-v model

A non-subsampling, image segmentation technology, applied in the field of image processing to achieve strong directional effects

Inactive Publication Date: 2018-09-07
LIAONING NORMAL UNIVERSITY
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, so far there are no related reports on segmentation methods combining non-subsampled shearlet transform and vector C-V model

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  • Image segmentation method based on non-subsampling shearlet transform and vector c-v model
  • Image segmentation method based on non-subsampling shearlet transform and vector c-v model
  • Image segmentation method based on non-subsampling shearlet transform and vector c-v model

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Embodiment Construction

[0036] Follow the steps below:

[0037] The Shearlet transform uses the downsampling operator in the multi-resolution representation process, so it will lose the spatial support, imitate the non-subsampled contourlet transform (Nonsubsampled Contourlet Transform, NSCT) construction method, and use the non-subsampled Laplacian pyramid algorithm Instead of the Laplacian pyramid algorithm, a Nonsubsampled Shearlet Transform (NSST) is constructed.

[0038] Define the C-V energy functional form as follows,

[0039] (1)

[0040] in H is the Heaviside function, defined as follows:

[0041]

[0042] Its distribution derivative is ;

[0043] for fixed and minimize about The function ,

[0044]

[0045] The Euler-Lagrange equation governing the mean curvature and the error term can be obtained by using the steepest downflow method ;

[0046] The vector C-V model has the following definition:

[0047]

[0048] in yes in the image etc. layer channel,...

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Abstract

The invention, which belongs to the image processing field, puts forward an image segmentation method based on non-down-sampling shearlet conversion and a vector C-V model. According to the method, multi-level decomposition is carried out on a given image by using non-down-sampling shear waves to obtain low-frequency and high-frequency components at different directions; the components are sent to a vector C-V model; a series of evolving curves distributed uniformly are initialized on the overall image; and an obtained energy functional is minimized to obtain a segmentation result. With the method, the segmentation effect is obvious; and objective evaluation quality and the visual effect are good.

Description

technical field [0001] The invention relates to the field of image processing, in particular to an image segmentation method based on non-subsampling Shearlet transform and vector C-V model. Background technique [0002] The importance and practicality of image segmentation has attracted more and more attention. At the same time, a large number of segmentation algorithms have been proposed, but so far there is no simple method that can be widely applied to all images. In other words, , the segmentation algorithm developed for a certain type of image is not necessarily applicable to other types of images. Mumfor-Shah (M-S) segmentation technique is a region-based image segmentation method. Chan and Vese simplified the energy functional in the M-S method by adding items related to the characteristics of the contour area, proposed the famous Chan-Vese (C-V) method, and extended the C-V model to the vector case, and the C-V model in the vector case inherits The advantage of th...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/10
Inventor 王相海方玲玲苏欣朱毅欢
Owner LIAONING NORMAL UNIVERSITY
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