Abstract
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.
Highlights
The haze or fog phenomenon frequently causes declining visibility in an outdoor environment and fuzzy acquired outdoor images
We propose an image dehazing method that focuses on the results of a series of applications of adaptive correction amendments
MODIFIED ARTIFICIAL MULTI-EXPOSURE FOR IMAGE DEHAZING In our study, three main improvements are proposed based on the original artificial multi-exposure fusion technique (AMEF) proposed by Galdran [47]: (1) the mean and standard deviation values of a hazy image are considered in the gamma correction; (2) homomorphic filtering is inserted into the Laplacian pyramid and Gaussian pyramid, which are employed to enhance the contrast of image; (3) A modified Laplacian filtering is proposed to calculate the contrast, in which the mixed second derivative is considered
Summary
The haze or fog phenomenon frequently causes declining visibility in an outdoor environment and fuzzy acquired outdoor images. In this circumstance, resorting to physical models of haze formation methods were utilized to overcome the fault He et al [9] and Zhu et al [12] employed the prior knowledge of an image to augment the contrast or eliminate weakened colours of foggy images. Based on the haloreduced dark channel prior, a new dehazing method for foggy image enhancement is proposed by Shi et al [33] (HRDIE). An adaptive approach is proposed to obtain the values of the parameters of gamma correction transformation, in which the mean and standard deviation values of each component (R, G, and B) of the colour image are employed. Compared with the reference Galdran [43], a new filter is utilized in the Laplacian pyramid and the experimental results demonstrate that the quality of the hazy image is improved.
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