Dense residual generative adversarial network capable of quickly removing rain

A network and residual technology, applied in biological neural network models, image enhancement, image analysis, etc., can solve problems such as excessive length and time-consuming residual rain lines, and achieve the goal of simplifying network structure, improving rain removal rate, and enhancing features. effect of contact

Pending Publication Date: 2021-01-22
BEIJING INSTITUTE OF TECHNOLOGYGY
View PDF6 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The present invention aims to provide a dense residual generation adversarial network for fast deraining. background detail information, reduce the time-consuming of deraining as much as possible, and establish a foundation for real-time deraining during the driving process of unmanned vehicles

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
  • Dense residual generative adversarial network capable of quickly removing rain
  • Dense residual generative adversarial network capable of quickly removing rain
  • Dense residual generative adversarial network capable of quickly removing rain

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0051] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. The components of the embodiments of the invention generally described and illustrated in the figures herein may be arranged and designed in a variety of different configurations.

[0052] Accordingly, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art wi...

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 dense residual generative adversarial network capable of quickly removing rain. The dense residual generative adversarial network comprises the following steps: establishingan algorithm operation environment; b, establishing a rain removal data set; c, designing a dense residual generator sub-network for quickly removing rain; d, designing a dense residual discriminatorsub-network for quickly removing rain; e, designing a discriminator and a generator loss function; and f, performing image post-processing and index calculation, and verifying the rain removal effectof the algorithm model. According to the invention, the operation and test environment of the whole algorithm is built, and the time consumption is reduced as much as possible while the rain removal effect is ensured and enough background details are reserved through the designed rain removal model. According to a result test, the rain removing duration of each image is about 0.02 s, and the rainremoving efficiency is greatly improved.

Description

technical field [0001] The invention relates to the technical field of visual environment perception for drone driving, in particular to a dense residual generation confrontation network for fast rain removal. Background technique [0002] For outdoor vision tasks, such as vision-based unmanned vehicle environment perception, pedestrian and road sign detection, tracking, road monitoring and other tasks, clean, clear and visible images are essential. Reliable visual images can help people complete various visual tasks more accurately and efficiently, while reducing or even avoiding unnecessary mistakes. However, under severe weather conditions, especially rainy weather, the visibility of images is seriously degraded, which brings great difficulties to various visual tasks. Therefore, the research on image deraining technology is imminent. However this task is very challenging. First of all, for heavy rain weather, rain will bring fog and blur the image, and it is difficult...

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): G06T5/00G06N3/04
CPCG06T5/002G06T2207/30252G06N3/044G06N3/045
Inventor 苑士华米颖李雪原
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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