Haze is the suspension of atmospheric particles which is sufficient to reduce the visibility. Image dehazing refers to the processing tasks that lessen this negative effect. In this work, an alternative approach to single-image dehazing is developed which skips solving the haze formation equation, while still respects its hypothesis. In this method, we generated multiple under-exposed images from a single hazy input, followed by a detail enhancement process. Such resulting images were then merged using weights calculated based on the Dark Channel Prior assumption and overcame luminance enhancement. The visual improvement has been validated by both qualitative and quantitative evaluations.
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