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| Content Provider | Directory of Open Access Journals (DOAJ) |
|---|---|
| Author | Mingye Ju Can Ding Y. Jay Guo Dengyin Zhang |
| Abstract | Haze is evident in most remote sensing (RS) images, particularly for the RS scenes captured in inclement weather, which severely hinders image interpretation. In this paper, two simple yet effective visibility restoration formulas are proposed for RGB-channel RS (RRS) images and multi-spectral RS (MSRS) images, respectively. More specifically, a robust gamma-correction-based dehazing model (RGDM) is first defined, which can better address the non-uniform illumination problem in hazy images. Then, the scene albedo restoration formula (SARF) used for the RRS images is obtained by imposing the existing prior knowledge on this RGDM, which enables us to simultaneously eliminate the interferences of haze and non-uniform illumination. In subsequence, according to Rayleigh’s law, an expanded restoration formula (E-SARF) is further developed for MSRS data. Using the proposed E-SARF, the spatially varying haze in each band can be thoroughly removed without using any extra information. The experiments are conducted on the challenging RRS and MSRS images, including images with non-uniform illumination, non-uniform haze distribution, and heavy haze. The results reveal that the SARF and the E-SARF are superior to most other state-of-the-art techniques in terms of both the recover quality and the implementation efficiency. |
| e-ISSN | 21693536 |
| DOI | 10.1109/ACCESS.2018.2889766 |
| Journal | IEEE Access |
| Volume Number | 7 |
| Language | English |
| Publisher | IEEE |
| Publisher Date | 2019-01-01 |
| Publisher Place | United States |
| Access Restriction | Open |
| Subject Keyword | Electrical Engineering. Electronics. Nuclear Engineering Heavy Haze Image Dehazing Implementation Efficiency Non-uniform Haze Non-uniform Illumination Remote Sensing |
| Content Type | Text |
| Resource Type | Article |
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