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

Multi-scale and multi-feature fusion feature pyramid network blind restoration method

A feature pyramid, multi-feature fusion technology, applied in neural learning methods, biological neural network models, character and pattern recognition, etc., can solve problems such as poor robustness and poor restoration performance, achieve high-quality restoration, and solve the problem of slow training. , to solve the effect of unstable results

Pending Publication Date: 2021-03-16
HENAN UNIVERSITY OF TECHNOLOGY
View PDF3 Cites 14 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] In view of the deficiencies in the above-mentioned background technology, the present invention proposes a multi-scale and multi-feature fusion feature pyramid network blind restoration method, which solves the technical problems of poor restoration performance and poor robustness of existing restoration methods

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
  • Multi-scale and multi-feature fusion feature pyramid network blind restoration method
  • Multi-scale and multi-feature fusion feature pyramid network blind restoration method
  • Multi-scale and multi-feature fusion feature pyramid network blind restoration method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0039] 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 making creative efforts belong to the protection scope of the present invention.

[0040] The present invention constructs Feature Pyramid Networks (Feature Pyramid Networks) based on the staged feature maps of ResNet (Residual Net), fully utilizes multi-scale feature maps, and proposes a multi-scale and multi-feature fusion feature through the fusion of feature pyramids. Pyramid network blind restoration method, and introduces the multi-scale structure similarity loss function as the constraint item of the generator network, and then obtains...

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 provides a multi-scale and multi-feature fusion feature pyramid network blind restoration method, which is used for solving the technical problems of poor restoration performance and poor robustness of an existing restoration method. The method comprises the following steps: firstly, acquiring N groups of clear images and blurred images from a data set; secondly, constructing a generative adversarial network model of a feature pyramid network and a dual-scale discriminator network; alternately training the feature pyramid network and the discriminator network by using N groups ofclear images and blurred images, and obtaining a final generative adversarial network model after a balance point is reached; and finally, inputting the blurred image to be processed into the final generative adversarial network model, and outputting a clear image. According to the method, the feature pyramid network is combined with the dual-scale discriminator, detail information loss is greatly avoided while the training speed is increased, finally, a multi-scale structure similarity loss function is introduced to further restrain image generation, and stable and high-quality restoration of the complex blurred image is achieved.

Description

technical field [0001] The invention relates to the technical field of blind restoration in the field of image processing and computer vision, in particular to a multi-scale and multi-feature fusion feature pyramid network blind restoration method. Background technique [0002] Blurred images are often seen in daily life. Due to the influence of imaging distance, imaging device resolution, camera shake and other factors, the image often degrades during the acquisition process, which leads to the occurrence of image blur, the most common of which is motion blur , severely restricts the development of medical imaging, traffic monitoring and target tracking, so it is particularly important to restore blurred images. [0003] When the blurred image is actually restored, the blur kernel is usually unknown, and only some prior information of the degraded image can be used to optimally estimate the original image under some restrictive rules. This method is called blind restoration...

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
IPC IPC(8): G06T7/246G06K9/46G06K9/62G06N3/04G06N3/08
CPCG06T7/248G06N3/08G06T2207/20081G06T2207/20084G06V10/40G06N3/045G06F18/22G06F18/24G06F18/253G06F18/214
Inventor 吴兰范晋卿
Owner HENAN UNIVERSITY OF TECHNOLOGY
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