SAR Image Segmentation Method Based on Ridgelet Filter and Convolution Structure Learning Model

A learning model and image segmentation technology, applied in the field of image processing, can solve problems such as poor regional consistency, inaccurate positioning of clustered areas, and reduced SAR image segmentation accuracy
CN106683102BActive Publication Date: 2019-07-23XIDIAN UNIV

Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Patents(China)
Current Assignee / Owner
XIDIAN UNIV
Publication Date
2019-07-23

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Abstract

The invention discloses an SAR image segmentation method based on ridgelet filters and a convolution structure model. The SAR image segmentation method based on ridgelet filters and a convolution structure model mainly solves the problem that in the prior art, segmentation of SAR images is not accurate. The SAR image segmentation method based on ridgelet filters and a convolution structure model includes the following steps: 1) sketching an SAR image, and obtaining a sketch image; 2) according to an area image of the SAR image, dividing the pixel subspace of the SAR image; 3) constructing a ridgelet filter set; 4) constructing a convolution structure learning model; 5) utilizing the SAR image segmentation method based on the ridgelet filters and the convolution structure model to segment the pixel subspace of a hybrid aggregation structure natural object; 6) based on the gathering feature of sketch lines, performing segmentation of an independent object; 7) based on visual sense semantic rules, performing segmentation of line object; 8) based on polynomial logic regression prior model, segmenting the pixel subspace of a formal area; and 9) combining the segmentation results. The SAR image segmentation method based on ridgelet filters and a convolution structure model can acquire good segmentation effect of SAR images, and can be used for semantic segmentation of the SAR images.
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Description

technical field

[0001] The invention belongs to the technical field of image processing, and further relates to a synthetic aperture radar (SAR) image segmentation method based on a ridgelet filter and a convolutional structure learning model in the technical field of target recognition. The invention can accurately segment the pixel subspace of mixed aggregation structures with different characteristics in the synthetic aperture radar SAR image, and can be used for target detection and recognition of the subsequent synthetic aperture radar SAR image. Background technique

[0002] Synthetic aperture radar (SAR) is an important progress in the field of remote sensing technology, which is used to obtain high-resolution images of the earth's surface. Compared with other types of imaging technologies, SAR has the advantages of all-time, all-weather, multi-band, multi-polarization, variable side angle of view and high resolution. It can also collect subsurface information throug...

Claims

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