Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Image super-resolution system based on empirical mode decomposition

An empirical mode decomposition and super-resolution technology, applied in the field of image processing, can solve the problems of low iris recognition accuracy and low image resolution, and achieve the effect of restoring global topology and fine texture

Pending Publication Date: 2022-08-02
BEIJING UNIV OF POSTS & TELECOMM
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The invention proposes an image super-resolution system based on empirical mode decomposition, which solves the problem of low image resolution and low iris recognition accuracy in related technologies

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
  • Image super-resolution system based on empirical mode decomposition
  • Image super-resolution system based on empirical mode decomposition
  • Image super-resolution system based on empirical mode decomposition

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0024] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts, all relate to the protection scope of the present invention.

[0025] The iris super-resolution problem is a challenging and highly ill-posed problem. Recently, CNN-based methods have dominated the mainstream due to their strong performance. Among them, the vast majority of existing methods exploit the complete CNN scheme to extensively mine prior information. However, the inherent characteristic of CNN is to preferentially extract features of low-frequency components, and then gradually focus on high-frequency components. T...

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 relates to the technical field of image processing, and provides an image super-resolution system based on empirical mode decomposition, and the system comprises an input module which is used for obtaining a first image; the first image is a low-resolution image; the feature extraction module is used for extracting features of the first image; the IMF prediction module is used for predicting a plurality of IMF feature maps according to the features of the first image; the plurality of IMF feature maps are located at different frequencies; the IMF prediction module comprises a plurality of parallel branches, each branch is a CNN filter bank, and the number of the branches is the same as that of the IMF feature maps; the reconstruction module is used for converting each IMF feature map into a new IMF according to a set amplification proportion to obtain a plurality of new IMFs; and superposing the plurality of new IMFs to obtain a second image, wherein the second image is a super-resolution image. According to the technical scheme, the problem of low iris recognition precision caused by low image resolution in the prior art is solved.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular, to an image super-resolution system based on empirical mode decomposition. Background technique [0002] General biometric identification is a high-tech technology that quantifies human physiology, behavior and other characteristic information into digital feature representation through a special biometric acquisition device, and then realizes personal identity identification and authentication through pattern recognition, neural network and other methods. Among them, compared with common biometric identification technologies such as face and fingerprint, iris has the advantages of high uniqueness, strong stability, good anti-counterfeiting, and non-contact, and is considered to be the most potential biometric identification technology. Iris recognition technology and products have been widely used in public security and justice, financial banking, social security welfare,...

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): G06T3/40G06T5/00G06V40/18G06V10/20G06N3/04G06V10/82
CPCG06T3/4053G06T3/4046G06T2207/20084G06T2207/30196G06N3/048G06N3/045G06T5/00
Inventor 何召锋王甲张志礼夏玉峰王宸
Owner BEIJING UNIV OF POSTS & TELECOMM
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products