Image Dehazing Based on Haziness Analysis

We present two haze removal algorithms for single image based on haziness analysis.One algorithm regards haze as the veil layer,and the other takes haze as the transmission.The former uses the illumination component image obtained by retinex algorithm and the depth information of the original image to remove the veil layer.The latter employs guided filter to obtain the refined haze transmission and separates it from the original image.The main advantages of the proposed methods are that no user interaction is needed and the computing speed is relatively fast.A comparative study and quantitative evaluation with some main existing algorithms demonstrate that similar even better quality results can be obtained by the proposed methods.On the top of haze removal,several applications of the haze transmission including image refocusing,haze simulation,relighting and 2-dimensional(2D)to 3-dimensional(3D) stereoscopic conversion are also implemented.

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.