title: A Bayesian framework for single image dehazing considering noise.
abstract: The single image dehazing algorithms in existence can only satisfy the demand for dehazing efficiency, not for denoising. In order to solve the problem, a Bayesian framework for single image dehazing considering noise is proposed. Firstly, the Bayesian framework is transformed to meet the dehazing algorithm. Then, the probability density function of the improved atmospheric scattering model is estimated by using the statistical prior and objective assumption of degraded image. Finally, the reflectance image is achieved by an iterative approach with feedback to reach the balance between dehazing and denoising. Experimental results demonstrate that the proposed method can remove haze and noise simultaneously and effectively.
authors.affiliation: Institute of Aeronautics and Astronautics Engineering, Air Force Engineering University, No. 1 Baling Road, Baqiao District, Xi'an 710038, China.
authors.forename: Dong
authors.initials: D
authors.lastname: Nan
authors.affiliation: Institute of Aeronautics and Astronautics Engineering, Air Force Engineering University, No. 1 Baling Road, Baqiao District, Xi'an 710038, China.
authors.forename: Du-yan
authors.initials: DY
authors.lastname: Bi
authors.affiliation: Institute of Aeronautics and Astronautics Engineering, Air Force Engineering University, No. 1 Baling Road, Baqiao District, Xi'an 710038, China.
authors.forename: Chang
authors.initials: C
authors.lastname: Liu
authors.affiliation: Institute of Aeronautics and Astronautics Engineering, Air Force Engineering University, No. 1 Baling Road, Baqiao District, Xi'an 710038, China.
authors.forename: Shi-ping
authors.initials: SP
authors.lastname: Ma
authors.affiliation: Institute of Aeronautics and Astronautics Engineering, Air Force Engineering University, No. 1 Baling Road, Baqiao District, Xi'an 710038, China.
authors.forename: Lin-yuan
authors.initials: LY
authors.lastname: He
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D007091:Image Processing, Computer-Assisted