SAR Image Segmentation Method Based on Deconvolution Network and Adaptive Inference Network

A deconvolution network and self-adaptive technology, applied in the field of image processing, can solve problems such as performance bottlenecks, laboriousness, and inability to better learn image structural features, and achieve strong adaptability, improved performance, and accurate image features automatically extracted Effect
CN105427313BActive Publication Date: 2018-03-06XIDIAN UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
XIDIAN UNIV
Publication Date
2018-03-06

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Abstract

The invention discloses a deconvolutional network and adaptive inference network based SAR image segmentation method and mainly solves the problem that human experience is required to extract image features in the prior art. The method is implemented by the steps of (1) sketching an SAR image; (2) extracting a complemented region graph of the SAR image; (3) training a deconvolutional network DNN for aggregation regions and homogeneous regions separately; (4) performing adaptive comparison inference on structural features of non-communicated regions in the aggregation and homogeneous regions to obtain segmentation results of the aggregation and homogeneous regions; (5) based on a watershed method, segmenting a structural region obtained in the step (2); and (6) combining the aggregation regions, the homogeneous regions and the structural region to obtain a segmentation result. According to the method, the segmentation result has relatively good regional consistency and the segmentation effect of the SAR image is improved. The method can be used for target detection and identification.
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Description

technical field

[0001] The invention belongs to the technical field of image processing, and further relates to a SAR image segmentation method, which can be used for target detection or image recognition. Background technique

[0002] SAR image segmentation refers to dividing the synthetic aperture radar SAR image into several disjoint regions according to the characteristics of grayscale, texture, structure and aggregation, and making these characteristics similar in the same region, but different in different regions. There are significant differences between regions. The purpose of synthetic aperture radar SAR image segmentation is to simplify or change the representation of the image, making the image easier to understand and analyze. Synthetic aperture radar SAR image segmentation is the basis of image understanding and interpretation, and the quality of segmentation directly affects subsequent analysis and recognition. In general, the more accurate the segmentation,...

Claims

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