Image Haze Removal Method Based on Histogram Gradient Feature Guidance
Bibliographic Data
| ID | 15499261 |
|---|---|
| Authors | Shiqi Huang (0000-0001-6243-8989, Guangzhou Vocational College of Science and Technology, corresponding author), Yucheng Zhang (0000-0001-9435-6734, Xi'an University of Technology), Ouya Zhang (Guangzhou Vocational College of Science and Technology) |
| Year | 2023 |
| Volume | 20 |
| Issue | 4 |
| Pages | 3030-3030 |
| Publication date | 2023-02-09 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Environmental Research and Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1661-7827 • E-ISSN: 1660-4601 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/ijerph20043030 |
| PMID | 36833724 |
| OpenAlex | W4319983380 |
| Language | EN |
| References cited | 1 |
Optical remote sensing images obtained in haze weather not only have poor quality, but also have the characteristics of gray color, blurred details and low contrast, which seriously affect their visual effect and applications. Therefore, improving the image clarity, reducing the impact of haze and obtaining more valuable information have become the important aims of remote sensing image preprocessing. Based on the characteristics of haze images, combined with the earlier dark channel method and guided filtering theory, this paper proposed a new image haze removal method based on histogram gradient feature guidance (HGFG). In this method, the multidirectional gradient features are obtained, the atmospheric transmittance map is modified using the principle of guided filtering, and the adaptive regularization parameters are designed to achieve the image haze removal. Different types of image data were used to verify the experiment. The experimental result images have high definition and contrast, and maintain significant details and color fidelity. This shows that the new method has a strong ability to remove haze, abundant detail information, wide adaptability and high application value
Computer vision · Feature (linguistics · Geography · Haze · Histogram · Image (mathematics · Preprocessor · Remote sensing · Advanced Image Fusion Techniques · Computer Science · Image Enhancement Techniques · Video Surveillance and Tracking Methods · Artificial Intelligence
| Citation velocity | historical |
|---|---|
| Highly cited | No |