Image restoration method and system based on a progressive learning strategy, medium and equipment

A repair method and image technology, applied in the field of image processing, can solve the problems of difficult and irregular area and high-frequency image detail repair, loss of semantic information, not considering image semantic information, etc., so as to maintain the integrity of image semantics and easy to repair. effects, effects that enhance the image restoration experience

Inactive Publication Date: 2021-04-09
SUN YAT SEN UNIV
View PDF0 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, most of the existing image repair methods generate images from the perspective of mathematics and physics, without considering the semantic information of the image, so they can only repair images with small damaged areas; repair images with large damaged areas When , there are problems that the restoration effect is poor, semantic information may be lost during the restoration process, and it is difficult to repair the details of irregular areas and high-frequency images.

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 restoration method and system based on a progressive learning strategy, medium and equipment
  • Image restoration method and system based on a progressive learning strategy, medium and equipment
  • Image restoration method and system based on a progressive learning strategy, medium and equipment

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0056] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0057] It should be noted that the numbering of the steps in the text is only for the convenience of explanation of the specific embodiments, and does not serve as a function of limiting the execution order of the steps. The method provided in this embodiment may be executed by a relevant server, and the description below takes the server as an execution subject as an example.

[0058] Such as Figure 1 to Figure 4 As shown, an image repair method based on a progr...

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 an image restoration method and system based on a progressive learning strategy, a storage medium and terminal device, and the method comprises the steps: inputting a to-be-restored image into a rough generation model, so as to obtain a rough generation result; extracting a feature map of the rough generation result to obtain a foreground feature map; and matching the foreground feature map with a background feature map, and reconstructing the foreground feature map by using the obtained background sample block with the highest matching degree with the foreground feature map. According to the method, when the large-area damaged area in the image is generated, the semantic integrity of the image is kept, clear details are generated, a good restoration effect is achieved on the image with the high structure, and therefore the image restoration experience of a user is improved.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to an image restoration method, system, computer-readable storage medium and terminal equipment based on a progressive learning strategy. Background technique [0002] Image inpainting is an important part of image restoration, which refers to filling information in the information-deficient areas on the image, and restoring the truth to the greatest extent, so that the restored image is visually and semantically authentic. Its purpose is to use the existing information of the image to restore the missing information. However, most of the existing image repair methods generate images from the perspective of mathematics and physics, without considering the semantic information of the image, so they can only repair images with small damaged areas; repair images with large damaged areas When , there are problems that the restoration effect is poor, semantic informatio...

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): G06T5/00G06K9/62G06N3/04G06N3/08
CPCG06T5/005G06N3/049G06N3/08G06T2207/10004G06N3/044G06N3/045G06F18/214
Inventor 韦舒心
Owner SUN YAT SEN UNIV
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

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap