A Novel Image Dehazing Algorithm via Adaptive Gamma-Correction and Modified AMEF

Captured images are usually influenced by fog or haze. In reality, image dehazing is challenging. This paper proposes a modified artificial multiple-exposure image fusion (AMEF) algorithm to remove the haze from an image. In the algorithm, first, an adaptive gamma-correction transform with the mean...

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Bibliographic Details
Main Authors: Liyun Zhuang, Yingshuang Ma, Yuanyang Zou, Guoxin Wang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9260183/
Description
Summary:Captured images are usually influenced by fog or haze. In reality, image dehazing is challenging. This paper proposes a modified artificial multiple-exposure image fusion (AMEF) algorithm to remove the haze from an image. In the algorithm, first, an adaptive gamma-correction transform with the mean and standard deviation values of each component of a hazy image is utilized to verify the intensities. Second, the homomorphic filtering algorithm is introduced into the Gaussian pyramid and Laplacian pyramid to compute the exposed accessible images. Last, a modified Laplacian filter method is presented to calculate the contrast of the exposed accessible images. Further, extensive experimental results demonstrate that the proposed algorithm has superior performance compared with that of some state-of-the-art methods, including higher contrast, richer details and a better visual effect in the dehazed image.
ISSN:2169-3536