Abstract: Due to the scattering effect of suspended particles in the atmosphere, foggy day images have reduced visibility and contrast significantly. Considering the loss of details and uneven defogging results of the contrast limited adaptive histogram equalization (CLAHE) algorithm, a curvelet transform and contrast adaptive clip histogram equalization (HE)-based foggy day image enhancement algorithm is proposed. The proposed algorithm transforms an image to the curvelet domain and enhances the image detail information via a nonlinear transformation of high frequency curvelet coefficients. After curvelet reconstruction, the contrast adaptive clip HE method is adopted to enhance the total image contrast and the foggy day image contrast and detail information. During the histogram clipping process, the clip limit value is adaptively selected based on image contrast and the sub-block image histogram variance. A comparative analysis of the foggy day image enhancement results are obtained by applying CLAHE, and some classical single image defogging algorithms and the proposed algorithm are also conducted to prove the effectiveness of the proposed algorithm with objective parameters.

Key words: defogging, clip limit, contrast adaptive clip HE, curvelets transform