Haze is one of the sources cause image degradation. Haze affects contrast and saturation of not only for the real world image, but also the road scenes. Most haze removal algorithms use an atmospheric scattering model for removing the effect of haze. Most of haze removal algorithms are based on the single scattering model which does not consider the blur in the haze image. In this paper, a novel haze removal algorithm using a multiple scattering model with deconvolution is proposed. The proposed algorithm considers blurring effect in the haze image. Down sampling of the haze image is also used for estimating the atmospheric light efficiently. The synthetic road scenes with and without haze are used to evaluate the performance of the proposed method. Experimental result demonstrates that the proposed algorithm performs better for restoring images affected by haze both qualitatively and quantitatively.
|Journal||IS and T International Symposium on Electronic Imaging Science and Technology|
|Publication status||Published - 2020 Jan 26|
|Event||2020 Autonomous Vehicles and Machines Conference, AVM 2020 - Burlingame, United States|
Duration: 2020 Jan 26 → 2020 Jan 30
Bibliographical noteFunding Information:
This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. 2019R1A2C2002167).
© 2020, Society for Imaging Science and Technology.
All Science Journal Classification (ASJC) codes
- Computer Graphics and Computer-Aided Design
- Computer Science Applications
- Human-Computer Interaction
- Electrical and Electronic Engineering
- Atomic and Molecular Physics, and Optics