Modified Image Haze Removal Algorithm Based on Dark Channel Prior

Hu, Junpeng; Li, Zuoyong; Chen, Xinwei

doi:10.1109/ispa-bdcloud-sustaincom-socialcom48970.2019.00235

Cited by 5 publications

(1 citation statement)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Among them, image enhancement-based defogging algorithms [5][6][7] take no consideration for the image degradation model but increase the contrast to obtain the visual defogged effect, resulting in distortion of defogged clear images. On the contrary, image restoration-based methods [8][9][10][11][12][13] consider the degradation process of foggy images, so the defogged clear images restored by these methods are closer to the real scene.…”

Section: Introductionmentioning

confidence: 99%

An Improved DCP-Based Image Defogging Algorithm Combined with Adaptive Fusion Strategy

Fang

Huang

et al. 2021

Mathematical Problems in Engineering

View full text Add to dashboard Cite

Dark channel prior (DCP) has been widely used in single image defogging because of its simple implementation and satisfactory performance. This paper addresses the shortcomings of the DCP-based defogging algorithm and proposes an optimized method by using an adaptive fusion mechanism. This proposed method makes full use of the smoothing and “squeezing” characteristics of the Logistic Function to obtain more reasonable dark channels avoiding further refining the transmission map. In addition, a maximum filtering on dark channels is taken to improve the accuracy of dark channels around the object boundaries and the overall brightness of the defogged clear images. Meanwhile, the location information and brightness information of fog image are weighed to obtain more accurate atmosphere light. Quantitative and qualitative comparisons show that the proposed method outperforms state-of-the-art image defogging algorithms.

show abstract