Tensor-model-based infrared dim target detecting method

A technology of weak and small targets and tensor model, applied in the field of image processing, can solve the problem of low detection accuracy of infrared weak and small targets, and achieve the effect of improving the accuracy

Active Publication Date: 2014-04-16
CHONGQING UNIV OF POSTS & TELECOMM
View PDF2 Cites 21 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] In view of this, the object of the present invention is to provide a tensor model-based infrared dim and small target detection method to solve the problem that the existing infrared dim and small target detection accuracy is not high

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Tensor-model-based infrared dim target detecting method
  • Tensor-model-based infrared dim target detecting method
  • Tensor-model-based infrared dim target detecting method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0040] The preferred embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings; it should be understood that the preferred embodiments are only for illustrating the present invention, rather than limiting the protection scope of the present invention.

[0041] Such as figure 1 As shown, a tensor model-based infrared weak and small target detection method proposed by the present invention can be used in infrared detection systems under complex backgrounds. By establishing a characteristic database for multi-character infrared weak and small targets, a multi-character tensor model is established according to the database, so as to achieve the purpose of detecting infrared weak and small targets through the model.

[0042] A tensor model-based infrared dim and small target detection method includes an offline training stage and an online detection stage, the offline training stage provides training samples for the online ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a tensor-model-based infrared dim target detecting method. The method comprises an off-line training stage and an online detecting stage, wherein the off-line training stage comprises S1, establishing a multi-characteristic sample database and S2, constructing high-order tensor models from the database, and the online detecting stage comprises S3, analyzing whether an unknown image sequence contains dim targets through the tensor models to achieve target detection. By establishing the tensor detection models, the tensor-model-based infrared dim target detecting method avoids the difficulty in identifying targets with complicated backgrounds and dim signal to noise ratios and can well detect targets in different scenarios and with dim signal to noise ratios and improve the detecting accuracy.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a method and system for detecting small and weak infrared targets. Background technique [0002] Most of the existing infrared faint target detection technologies only realize the target detection work with high signal-to-noise ratio in a simple background. These target detection algorithms have a lot of deficiencies, such as high false alarm rate in complex background or low detection probability in the case of low target signal-to-noise ratio. [0003] At present, the infrared faint target detection methods can be divided into three categories: one is the target detection method based on the background prediction model; the other is the detection method based on the design of the time domain motion characteristics of the target; the third is the target detection method based on the mathematical transformation domain. [0004] The target detection based on the backgrou...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06K9/62
Inventor 高陈强田超李璐星陈良曹杰
Owner CHONGQING UNIV OF POSTS & TELECOMM
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products