Single
Image Defogging by Multi-level Depth Inference and Airlight Estimation Abstract
This paper presents an automatic method for the defogging from a single haze image. To recover a foggy image, an accurate depth map is estimated from a multi-level inference method, which fuses depth maps with different sizes of patches by dark channel prior. Markov random field (MRF) is applied to label the depth level in adjacent region for the compensation of wrong estimated regions. Airlight is automatically estimated as the deepest and largest area from the MRF labeled result. The accurate estimation of airlight provides good restoration with respect to visibility and contrast but without oversaturating. The algorithm is verified by a handful of foggy and hazy images. Experimental results demonstrate that the defogging method can recover high-quality images through accurate estimation of depth map and airlight. Experimatal Result
Results and Depth maps More Results Iterative defogging Comparisons: Demo Video Related Material
1. ICGIP 2012 presentation slides 2. CVGIP 2012 presentation slides Reference [1] Y. K. Wang, C. T. Fan, and C. W. Chang, "Accurate Depth Estimation for Image Defogging using Markov Random Field," in 4th International Conference on Graphic and Image Processing, Singapore, 2012 [2] Y. K. Wang, C. T. Fan, and C. W. Chang, "Single Image
Defogging by Multi-level Depth Estimation and Automatic Airlight
Extraction," The 25th IPPR Conference on Computer Vision, Graphics, and Image Processing, Taiwan, 2012
[3] K.He, J. Sun, and X. Tang, "Single Image Haze Removal using Dark Channel Prior," in CVPR, 2009. [4] J. Kopf, B. Neubert, B. Chen, M. Cohen, D. Cohen-Or, O. Deussen, M. Uyttendaele, and D. Lischinski, "Deep Photo: Mo del-Based Photograph Enhancement and Viewing," ACM Transactions on Graphics, 2008.
[5] R. T. Tan, "Visibility in Bad Weather from a Single Image," in CVPR, 2008.
[6] R. Fattal, "Single Image Dehazing," ACM Transactions on Graphics, 2008. |