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Articles

Dehazing of remote sensing images using improved restoration model based dark channel prior

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Pages 282-292 | Received 06 Feb 2017, Accepted 08 May 2017, Published online: 25 May 2017
 

ABSTRACT

Haze degrades visual information of remotely sensed images. Therefore, haze removal is a demanding and significant task for visual multispectral information improvement. The existing haze removal techniques utilize different restrictions and before restoring hazy images in an efficient manner. The review of existing haze removal methods demonstrates that the haze-free images suffer from colour distortion and halo artefacts problems. To solve these issues, an improved restoration model based dark channel prior is proposed in this paper. The proposed technique has redefined transmission map, with the aim to reduce the colour distortion problem. The modified joint trilateral filter is also utilized to improve the coarse estimated atmospheric veil. The experimental results reveal that the proposed approach provides visually significant haze-free images and also preserves the significant detail.

Disclosure statement

No potential conflict of interest was reported by the authors.

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