A High-Fidelity Haze Removal Method Based on HOT for Visible Remote Sensing Images
AbstractSpatially varying haze is a common feature of most satellite images currently used for land cover classification and mapping and can significantly affect image quality. In this paper, we present a high-fidelity haze removal method based on Haze Optimized Transformation (HOT), comprising of three steps: semi-automatic HOT transform, HOT perfection and percentile based dark object subtraction (DOS). Since digital numbers (DNs) of band red and blue are highly correlated in clear sky, the R-squared criterion is utilized to search the relative clearest regions of the whole scene automatically. After HOT transform, spurious HOT responses are first masked out and filled by means of four-direction scan and dynamic interpolation, and then homomorphic filter is performed to compensate for loss of HOT of masked-out regions with large areas. To avoid patches and halo artifacts, a procedure called percentile DOS is implemented to eliminate the influence of haze. Scenes including various land cover types are selected to validate the proposed method, and a comparison analysis with HOT and Background Suppressed Haze Thickness Index (BSHTI) is performed. Three quality assessment indicators are selected to evaluate the haze removed effect on image quality from different perspective and band profiles are utilized to analyze the spectral consistency. Experiment results verify the effectiveness of the proposed method for haze removal and the superiority of it in preserving the natural color of object itself, enhancing local contrast, and maintaining structural information of original image. View Full-Text
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Jiang, H.; Lu, N.; Yao, L. A High-Fidelity Haze Removal Method Based on HOT for Visible Remote Sensing Images. Remote Sens. 2016, 8, 844.
Jiang H, Lu N, Yao L. A High-Fidelity Haze Removal Method Based on HOT for Visible Remote Sensing Images. Remote Sensing. 2016; 8(10):844.Chicago/Turabian Style
Jiang, Hou; Lu, Ning; Yao, Ling. 2016. "A High-Fidelity Haze Removal Method Based on HOT for Visible Remote Sensing Images." Remote Sens. 8, no. 10: 844.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.