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Segmentation Method of Spatial Object Isar Image Parts Based on CGAN

A space target and image technology, applied in image analysis, graphic image conversion, image data processing, etc., can solve the problem of low segmentation accuracy of ISAR image components, and achieve the effect of improving segmentation accuracy

Active Publication Date: 2022-04-19
XIDIAN UNIV
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Problems solved by technology

[0005] The purpose of the present invention is to address the shortcomings of the above-mentioned prior art, and propose a CGAN-based space object ISAR image component segmentation method, which is used to solve the problem of low segmentation accuracy of space object ISAR image components in the prior art

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  • Segmentation Method of Spatial Object Isar Image Parts Based on CGAN
  • Segmentation Method of Spatial Object Isar Image Parts Based on CGAN
  • Segmentation Method of Spatial Object Isar Image Parts Based on CGAN

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Embodiment Construction

[0035] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0036] refer to figure 1 , the present invention comprises the following steps:

[0037] (1) Generate training data set and test data set:

[0038] (1a) M pieces of ISAR images with a size of 256×256 randomly selected from the space object ISAR image data set, the present invention adopts the Labelme image labeling tool developed by the MIT Computer Science and Artificial Intelligence Laboratory, and M pieces of size are 256 The solar panels and the main body in the ×256 ISAR image are marked with different colors at the pixel level, and each labeled ISAR image with the ground truth is up, down, left, right, upper left, lower left, upper right, and lower right Translate in eight directions to obtain M × 8 translation ISAR images with real labels; in this embodiment, the translation distances in eight directions are 25;

[0039] (1b...

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Abstract

The present invention proposes a method for segmenting spatial target ISAR image components based on conditional generative confrontation network CGAN, which is used to solve the problem of low accuracy of ISAR image segmentation in the prior art. The implementation steps are: generating training data sets and test data sets; Construct the conditional generative confrontation network CGAN model; iteratively train the conditional generative confrontation network CGAN; test the trained conditional generative confrontation network CGAN; segment and predict the spatial target ISAR image components in the segmented image. The present invention utilizes the confrontation game process of the conditional generation confrontation network CGAN to realize the global mapping from the ISAR image to its label, and constructs the high-frequency components of the predicted segmented image well. At the same time, it also uses L 1 The loss constructs the low-frequency components of the predicted segmented image, making the predicted segmented image and the overall similarity of the label, which effectively improves the segmentation accuracy of spatial object ISAR image components.

Description

technical field [0001] The invention belongs to the technical field of radar image processing, and relates to an ISAR image segmentation method, in particular to a CGAN-based space target ISAR image component segmentation method, which can be used in the fields of space target attitude estimation, space target recognition and the like. Background technique [0002] Inverse Synthetic Aperture Radar (ISAR, Inverse Synthetic Aperture Radar) is an important branch in the development process of synthetic aperture radar, which has the ability of all-day, all-weather and long-distance imaging. As countries around the world pay more and more attention to space resources, the development of space resources has become a hot spot, and the trend of space operations will gradually intensify in the future. Space targets have become a research hotspot in the field of radar. By analyzing the acquired ISAR images of space targets, we can To realize the determination of the type, size, materi...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/11G06T7/136G06T3/40G06N3/04G06K9/62G06V10/774
CPCG06T7/11G06T3/4038G06T7/136G06N3/045G06F18/214
Inventor 杜兰吕国欣石钰郭昱辰
Owner XIDIAN UNIV
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