Abstract
The scattering of atmospheric particles significantly alters images captured under hazy weather condition. Images appear distorted, blurry and low in contrast attenuation, which extensively affects computer vision systems. There has been development of several prior based methods to address this problem. However, these methods come at a high computational cost. We present a fast, single image dehazing method based on dark channel prior and Rayleigh scattering. Firstly, we present a simple but effective methodology for estimating the atmospheric light through the computation of average, minimum and maximum of the pixels in each of the three RGB colour channels. Then, using the theory of Rayleigh scattering, we model a scattering coefficient to estimate the initial transmission map. Also, a fast-guided filter is adopted to refine the initial transmission map due to inaccurate halo edges. Finally, we restore the haze-free image through the atmospheric scattering model. Extensive qualitative and computational experiments on hazy outdoor images demonstrate that the proposed method produces excellent results whiles achieving a faster processing time.
Highlights
Outdoor images are affected by natural and artificial adverse weather condition such as mist, smoke, haze, fog, and smog due to the discernibility-diminishing aerosols, which substantially cause colour change, image degradation, and scene darkening, among others
We propose a simple but fast-single image dehazing algorithm based on the dark channel prior (DCP) theory and Rayleigh scattering to reduce computational time whiles, achieving high-quality dehazed images
BACKGROUND we present concepts such as atmospheric scattering, dark channel prior (DCP) and Rayleigh scattering used for the framework of the proposed technique for single image dahazing
Summary
Outdoor images are affected by natural and artificial adverse weather condition such as mist, smoke, haze, fog, and smog due to the discernibility-diminishing aerosols, which substantially cause colour change, image degradation, and scene darkening, among others. These aerosols are the arrangement of solid or fluid particles suspended by a blend of gases [1]. The atmospheric scattering model has several unknown parameters which equates to the number of pixels in an image In this way, the immediate estimation of t(i,j) from I(i,j) is restrictive with no earlier assumptions.
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