Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Efficient haze removal method suitable for large-scale optical remote sensing image

An optical remote sensing, large-scale technology, applied in the field of large-scale optical remote sensing image haze removal, medium and low spatial resolution optical remote sensing imagery

Active Publication Date: 2020-06-30
莫登奎
View PDF6 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] To sum up, the problem existing in the existing technology is: how to construct a more accurate HTM considering the interference effect of bright ground objects? Especially for VHR satellite imagery with complex fog and haze in densely built-up areas, there is no report on this aspect yet

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
  • Efficient haze removal method suitable for large-scale optical remote sensing image
  • Efficient haze removal method suitable for large-scale optical remote sensing image
  • Efficient haze removal method suitable for large-scale optical remote sensing image

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0045]In order to make the object, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0046] The main challenge at present is how to construct a more accurate HTM considering the interference effect of bright ground objects, especially for VHR satellite images with complex haze in densely built areas, which has not been reported yet.

[0047] Aiming at the haze phenomenon in VHR multi-spectral remote sensing images, the present invention provides a new simple and general haze detection and removal method, which will be described in detail below in conjunction with the accompanying drawings.

[0048] like figure 1 As shown, the efficient method for removing haze from large-scale optical remote sensing images ...

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 belongs to the technical field of high-resolution optical remote sensing image preprocessing, and discloses an efficient method suitable for large-scale optical remote sensing image hazeremoval. The method comprises the following steps: inputting original remote sensing data and default parameters; calculating a pixel intensity norm; calculating a haze thickness image; calculating ahaze thickness mask image; calculating a refined haze thickness image; extracting a large-patch haze image Haze_map_majorsity and a pixel position map, and obtaining a large-patch haze image Haze_map_majorsity; calculating a haze sensitive pixel HTMi (x, y); haze is removed; haze compensation. According to the efficient haze removal method suitable for large-scale optical remote sensing images, HTM is estimated from an average vector L2-norm of a given sample window blue band, a compensation strategy of fog-free pixels and fog pixels is improved, the method has been successfully applied to various VHR optical satellite images with complex haze coverage in a dense area, and a reference value is provided for haze removal and haze degree evaluation of a remote sensing image.

Description

technical field [0001] The invention belongs to the technical field of high-resolution (Very High Resolution, VHR) optical remote sensing image preprocessing, and in particular relates to an efficient method for removing haze from large-scale optical remote sensing images, and is also applicable to medium and low spatial resolution optical remote sensing image. Background technique [0002] Currently, when acquiring imagery from satellites or aircraft, different characteristics of the atmosphere can lead to poor image quality and visual interpretability. Water vapor and water droplets, smog, dust, and aerosols are all considered "haze" because they have similar effects in reducing image quality through scattering and spectral distortion in the visible spectral band, greatly compromising useful analysis. Contrary to the clouds in the image, the transparency of the image affected by haze can be compensated to a certain extent by image restoration techniques. Therefore, there...

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): G06T5/00G06T7/13
CPCG06T7/13G06T2207/10032G06T2207/30168G06T5/73
Inventor 莫登奎
Owner 莫登奎
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
Eureka Blog
Learn More
PatSnap group products

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