Accelerated haze removal for a single image by dark channel prior

Haze scatters light transmitted in the air and reduces the visibility of images.Dealing with haze is still a challenge for image processing applications nowadays.For the purpose of haze removal,we propose an accelerated dehazing method based on single pixels.Unlike other methods based on regions,our method estimates the transmission map and atmospheric light for each pixel independently,so that all parameters can be evaluated in one traverse,which is a key to acceleration.Then,the transmission map is bilaterally filtered to restore the relationship between pixels.After restoration via the linear hazy model,the restored images are tuned to improve the contrast,value,and saturation,in particular to offset the intensity errors in different channels caused by the corresponding wavelengths.The experimental results demonstrate that the proposed dehazing method outperforms the state-of-the-art dehazing methods in terms of processing speed.Comparisons with other dehazing methods and quantitative criteria(peak signal-to-noise ratio,detectable marginal rate,and information entropy difference)are introduced to verify its performance.

Image Defogging Algorithm Based on Sky Region Segmentation and Dark Channel Prior

Based on image segmentation and the dark channel prior,this paper proposes a fog removal algorithm in the HSI color space.Usually,the dark channel prior based defogging methods easily produce color distortion and halo effect when applied on images with a large sky area,because the sky region does not meet the prior assumption.For this reason,our method presents a new threshold sky region segmentation algorithm using the initial transmission map of the intensity component I.Based on the segmentation result,the initial transmission map is modified in turn,and finally refined by the guided filter.The saturation components S is reconstructed using the low frequencies of the V-transform to reduce noise,and stretched by multiplying a constant related to the initial transmission map.Experimental results show that the proposed algorithm has low time complexity and compelling fog removal result in both visual effect and quantitative measurement.

Improved single image dehazing using dark channel prior

An improved single image dehazing method based on dark channel prior and wavelet transform is proposed. This proposed method employs wavelet transform and guided filter instead of the soft matting procedure to estimate and refine the depth map of haze images. Moreover, a contrast enhancement method based on just noticeable difference(JND) and quadratic function is adopted to enhance the contrast for the dehazed image, since the scene radiance is usually not as bright as the atmospheric light,and the dehazed image looks dim. The experimental results show that the proposed approach can effectively enhance the haze image and is well suitable for implementing on the surveillance and obstacle detection systems.