SAR (synthetic aperture radar) image segmentation method based on depth autoencoders and area charts

A self-encoder and image segmentation technology, applied in the field of image processing, can solve the problems of segmentation representation, difficulty, and less research, and achieve the effect of good edge consistency, regional consistency and edge consistency, and accurate segmentation.

Active Publication Date: 2015-03-04
XIDIAN UNIV
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Problems solved by technology

However, in practical applications, first of all, it will be in trouble due to the inability to obtain ideal training data, and secondly, it is difficult to apply the learned features to the region for segmentation and r

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  • SAR (synthetic aperture radar) image segmentation method based on depth autoencoders and area charts
  • SAR (synthetic aperture radar) image segmentation method based on depth autoencoders and area charts
  • SAR (synthetic aperture radar) image segmentation method based on depth autoencoders and area charts

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Embodiment Construction

[0030] The present invention will be further described below in conjunction with the accompanying drawings of the embodiments.

[0031] refer to Figure 1-2 , the detailed implementation steps of the present invention are as follows:

[0032] Step 1, obtain the area map of the SAR image.

[0033] (1.1) Input a picture such as image 3 For the SAR image shown, the sketch of the SAR image is obtained according to the initial sketch model, such as Figure 4 As shown, the initial sketch model is derived from computer vision theory, and is a model that uses visual primitives to abstract images, and can be used to extract sketches of images;

[0034] (1.2) Use the ray method to complete the sketch line segment in the sketch map to obtain the area map, such as Figure 5 As shown in , the ray method is a method of emitting rays to all sketch line segments in the sketch map to find the boundary of the region, which can be used for region map extraction;

[0035] (1.3) Map the regi...

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Abstract

The invention discloses an SAR (synthetic aperture radar) image segmentation method based on depth autoencoders and area charts, and mainly solves the problems of inaccurate and careless segmentation in the prior art. The method comprises the following steps: 1, obtaining an SAR image sketch according to an initial sketch model, complementing sketch segments to obtain the area charts, mapping the area charts to an original chart to obtain gathering, homogeneous and structure areas; 2, training the gathering and homogenous areas by the different depth autoencoders respectively to obtain expressions corresponding to all points, and cascading last two encoding layers to serve as the characteristics of the points; 3, constructing dictionaries for the gathering and homogenous areas respectively, projecting the characteristics of the points to the corresponding dictionaries, and gathering area characteristics of sub-areas; 4, clustering the sub-area characteristics of two types of areas respectively; 5, segmenting the structure area by superpixel binning under the guidance of the sketch segments; 6, combining the segmentation results of the areas to finish SAR image segmentation. The method has the advantages of accurate and careful segmentation, and can be used for target identification.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a method for segmenting SAR images by a deep self-encoder in a deep learning method and a region map of a SAR image, which can be used to further identify and classify SAR images. Background technique [0002] Synthetic Aperture Radar (SAR) is a radar that uses the relative motion of the radar and the target to synthesize a smaller real antenna aperture into a larger equivalent antenna aperture by data processing. It has all-weather and all-time stable high-resolution imaging The SAR image is an image formed by a larger radar antenna through radar aperture synthesis, and its characteristics make it a very valuable image that is widely used in many fields such as military affairs, agriculture, navigation, and geography. Image segmentation is the technology and process of dividing an image into several interconnected and disjoint regions with unique properties ...

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Application Information

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IPC IPC(8): G06T7/00G06K9/62G06T7/11
CPCG06T7/11G06T2207/20081G06T2207/20152
Inventor 刘芳石西建李玲玲焦李成郝红侠石俊飞杨淑媛段一平张向荣尚荣华
Owner XIDIAN UNIV
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