SAR Image Segmentation Method Based on Depth Autoencoder and Region Map

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 ...

AI Technical Summary

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 representation. Therefore, how to effectively combine deep learning methods for SAR image segmentation It is a very difficult problem to obtain a very ideal effect, and there are very few studies based on this technology

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