Image defogging method and device
An image and foggy technology, applied in the field of image processing, can solve the problems of white borders extended by depth jumps, overall dark images, etc., and achieve the effect of strong ability, bright colors, and multiple layers
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment 1
[0078] figure 1 The implementation flow of the image defogging method provided by Embodiment 1 of the present invention is shown, and the details are as follows:
[0079] In step S101 , artificially add fog to the fog-free image to generate a fog-containing image.
[0080] In the embodiment of the present invention, for a foggy image, it is difficult to obtain its corresponding fog-free image for training. In order to solve this problem, the embodiment of the present invention adopts the artificial fogging method to add fog to the non-fogged image to produce a foggy image.
[0081] One advantage of using artificially fogged images is that the transmittance of foggy images can be easily obtained for the training of multi-scale deep convolutional networks.
[0082] Among them, the scene depth of the fog-free image and the set fog concentration can be obtained first, and then the fog concentration and the scene depth can be converted into transmittance, and finally according to...
Embodiment 2
[0117] Figure 6 A specific structural block diagram of the image defogging device provided by Embodiment 2 of the present invention is shown. For convenience of description, only parts related to the embodiment of the present invention are shown. The image defogging device 6 includes: a manual fogging unit 61 , a model training unit 62 , a transmittance output unit 63 and an image defogging unit 64 .
[0118] Wherein, the artificial fogging unit 61 is used for artificially fogging the non-foggy image to generate the foggy image;
[0119] A model training unit 62, configured to input the foggy image and the transmittance of the foggy image to a deep convolutional network or a multi-scale deep convolutional network, and train the deep convolutional network or the multi-scale deep convolutional network, until the error between the transmittance output by the deep convolutional network or the multi-scale deep convolutional network and the transmittance of the foggy image is less...
PUM
Abstract
Description
Claims
Application Information
- R&D Engineer
- R&D Manager
- IP Professional
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com