A Bayesian Framework for Single Image Dehazing considering Noise

Joint Authors

Nan, Dong
Bi, Du-yan
Liu, Chang
Ma, Shi-ping
He, Lin-yuan

Source

The Scientific World Journal

Issue

Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-13, 13 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2014-08-19

Country of Publication

Egypt

No. of Pages

13

Main Subjects

Medicine
Information Technology and Computer Science

Abstract EN

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.

American Psychological Association (APA)

Nan, Dong& Bi, Du-yan& Liu, Chang& Ma, Shi-ping& He, Lin-yuan. 2014. A Bayesian Framework for Single Image Dehazing considering Noise. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-13.
https://search.emarefa.net/detail/BIM-1050513

Modern Language Association (MLA)

Nan, Dong…[et al.]. A Bayesian Framework for Single Image Dehazing considering Noise. The Scientific World Journal No. 2014 (2014), pp.1-13.
https://search.emarefa.net/detail/BIM-1050513

American Medical Association (AMA)

Nan, Dong& Bi, Du-yan& Liu, Chang& Ma, Shi-ping& He, Lin-yuan. A Bayesian Framework for Single Image Dehazing considering Noise. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-13.
https://search.emarefa.net/detail/BIM-1050513

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1050513