JOURNAL ARTICLE

Single color image dehazing using sparse priors

Abstract

We present a new algorithm for removing the haze effects from a single color image. By introducing an additive noise argument in the degradation image model, we establish a unified probabilistic framework for the clear day image and the atmosphere transmission. Then we use an alternative optimization method to approximate the MAP estimators of these two variables iteratively. Experimental results demonstrate the efficiency of the proposed method on restoring the true scene colors and contrast.

Keywords:
Computer science Image (mathematics) Artificial intelligence Prior probability Image restoration Noise (video) Computer vision Color image Estimator Contrast (vision) Probabilistic logic Algorithm Pattern recognition (psychology) Image processing Bayesian probability Mathematics Statistics

Metrics

24
Cited By
1.28
FWCI (Field Weighted Citation Impact)
13
Refs
0.80
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Image Enhancement Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image Fusion Techniques
Physical Sciences →  Engineering →  Media Technology
Advanced Image Processing Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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