Automatic Exposure Correction of Consumer Photographs

  • Lu Yuan
  • Jian Sun
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7575)


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.


Input Image Exposure Evaluation Histogram Equalization Zone Region Tone Mapping 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Lu Yuan
    • 1
  • Jian Sun
    • 1
  1. 1.Microsoft Research AsiaChina

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