Haze/fog is a common weather phenomenon that may exist in both day and night conditions and presents loss of contrast in captured images. For an imaging device to capture good quality photographs, it is necessary that the captured scene be well-illuminated. But sometimes due to bad illumination, which may be due to natural or manmade conditions, the captured images present degradation. To solve the ill effects of bad illumination, we propose an image enhancement algorithm that sufficiently deals with both hazy and dark images. By combining dynamic stochastic resonance and a fusion method based on illumination estimation, a local contrast enhancement of the image as seen in the fused image is achieved in the first stage. While images that are only dark are sufficiently illuminated, the effect of haze in day/night hazy images remains unchanged. In the second stage, we solve this issue by modifying the atmospheric degradation model to reduce the effect of haze. The proposed method does not rely on the estimation of atmospheric light; rather, a mean preserving algorithm to restore the mean brightness of the image has been applied. The qualitative and quantitative experiments validate the efficacy and robustness of the proposed method.