Automatic Exposure Correction of Consumer Photographs

We study the problem of automatically correcting the exposure of an input image. Generic auto-exposure correction methods usually fail in individual over-/under-exposed regions. Interactive corrections may fix this issue, but adjusting every photograph requires skill and time. This paper will automate the interactive correction technique by estimating the image specific S-shaped non-linear tone curve that best fits the input image. Our first contribution is a new Zone-based region-level optimal exposure evaluation, which would consider both the visibility of individual regions and relative contrast between regions. Then a detail-preserving S-curve adjustment is applied based on the optimal exposure to obtain the final output. We show that our approach enables better corrections comparing with popular image editing tools and other automatic methods.

[1]  L. Blake.  THE NEGATIVE , 2020, A Silvan Tomkins Handbook.

[2]  S. Shimizu,et al.  A New Algorithm Of Exposure Control Based On Fuzzy Logic For Video Cameras , 1992, IEEE 1992 International Conference on Consumer Electronics Digest of Technical Papers.

[3]  S. A. Bhukhanwala,et al.  Automated global enhancement of digitized photographs , 1994 .

[4]  Karel J. Zuiderveld,et al.  Contrast Limited Adaptive Histogram Equalization , 1994, Graphics Gems.

[5]  S. Pizer,et al.  The Image Processing Handbook , 1994 .

[6]  Zia-ur Rahman,et al.  Properties and performance of a center/surround retinex , 1997, IEEE Trans. Image Process..

[7]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[8]  ShirleyPeter,et al.  Photographic tone reproduction for digital images , 2002 .

[9]  E. Reinhard.  Photographic Tone Reproduction for Digital Images , 2002 .

[10]  Shree K. Nayar,et al.  Adaptive dynamic range imaging: optical control of pixel exposures over space and time , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[11]  Sebastiano Battiato,et al.  Automatic Image Enhancement by Content Dependent Exposure Correction , 2004, EURASIP J. Adv. Signal Process..

[12]  Robert Sobol,et al.  Improving the Retinex algorithm for rendering wide dynamic range photographs , 2002, IS&T/SPIE Electronic Imaging.

[13]  Daniel P. Huttenlocher,et al.  Efficient Graph-Based Image Segmentation , 2004, International Journal of Computer Vision.

[14]  Vladimir Brajovic,et al.  Brightness perception, dynamic range and noise: a unifying model for adaptive image sensors , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[15]  Hiroaki Kotera,et al.  Dynamic range compression preserving local image contrast for digital video camera , 2005, IEEE Transactions on Consumer Electronics.

[16]  Zeev Farbman,et al.  Interactive local adjustment of tonal values , 2006, ACM Trans. Graph..

[17]  Ming Yang,et al.  Face detection for automatic exposure control in handheld camera , 2006, Fourth IEEE International Conference on Computer Vision Systems (ICVS'06).

[18]  I. Safonov.  Automatic correction of amateur photos damaged by backlighting , 2006 .

[19]  Hiroshi Nagahashi,et al.  Cross-Parameterization for Triangular Meshes with Semantic Features , 2007 .

[20]  Jan Kautz,et al.  Exposure Fusion , 2007, 15th Pacific Conference on Computer Graphics and Applications (PG'07).

[21]  Sanjit K. Mitra,et al.  Enhancement of Color Images by Scaling the DCT Coefficients , 2008, IEEE Transactions on Image Processing.

[22]  Wojciech Matusik,et al.  Image restoration using online photo collections , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[23]  Jian Sun,et al.  SkyFinder: attribute-based sky image search , 2009, ACM Trans. Graph..

[24]  David A. Forsyth,et al.  Generalizing motion edits with Gaussian processes , 2009, ACM Trans. Graph..

[25]  Seong-Dae Kim,et al.  Dynamic range compression based on statistical analysis , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

[26]  Roberto Manduchi,et al.  One-Shot Optimal Exposure Control , 2010, ECCV.

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

[28]  Dani Lischinski,et al.  Personalization of image enhancement , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[29]  Thomas Deselaers,et al.  ClassCut for Unsupervised Class Segmentation , 2010, ECCV.

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

[31]  Sylvain Paris,et al.  Learning photographic global tonal adjustment with a database of input/output image pairs , 2011, CVPR 2011.

[32]  Julie Dorsey,et al.  Understanding and improving the realism of image composites , 2012, ACM Trans. Graph..