Correction of over-exposure using dark channel prior and image fusion technique

A novel over exposure (OE) correction method using Dark Channel Prior and image fusion technique is proposed in this work. Assuming an OE image can be modeled as a normal exposure image added up with a layer of asymmetrical haze, its submerged information in OE regions is enhanced by haze removal model. With image fusion technique, the obtained texture in OE regions is used to restore the over exposure. Experiments show that our method works well in submerged information restoration without increasing pseudo-information and over Saturation.

[1]  Yuan Cheng,et al.  Correcting over-exposure in photographs , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[2]  Jiejie Zhu,et al.  Automatic Correction of Saturated Regions in Photographs using Cross‐Channel Correlation , 2009, Comput. Graph. Forum.

[3]  S. Pei,et al.  Edge-preserving image decomposition using L1 fidelity with L0 gradient , 2012, SIGGRAPH Asia Technical Briefs.

[4]  Narendra Ahuja,et al.  Split Aperture Imaging for High Dynamic Range , 2004, International Journal of Computer Vision.

[5]  Chang-Su Kim,et al.  Optimized contrast enhancement for real-time image and video dehazing , 2013, J. Vis. Commun. Image Represent..

[6]  Zia-ur Rahman,et al.  A multiscale retinex for bridging the gap between color images and the human observation of scenes , 1997, IEEE Trans. Image Process..

[7]  Ramesh Raskar,et al.  Why I Want a Gradient Camera , 2022 .

[8]  Alexei A. Efros,et al.  Fast bilateral filtering for the display of high-dynamic-range images , 2002 .

[9]  S. Süsstrunk,et al.  Frequency-tuned salient region detection , 2009, CVPR 2009.

[10]  Frédo Durand,et al.  Noise-optimal capture for high dynamic range photography , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[11]  Jian Sun,et al.  Guided Image Filtering , 2010, ECCV.