1 / 12

Context-aware Exposure Auto-correction

Context-aware Exposure Auto-correction. Global exposure auto-correction. over-exposed. under-exposed. low-contrast. input. automatic histogram stretching. Global exposure auto-correction. Detection: valid histogram range < threshold Method: stretch histogram, adjust gamma curve.

Sophia
Download Presentation

Context-aware Exposure Auto-correction

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Context-aware Exposure Auto-correction

  2. Global exposure auto-correction over-exposed under-exposed low-contrast input automatic histogram stretching

  3. Global exposure auto-correction • Detection: valid histogram range < threshold • Method: stretch histogram, adjust gamma curve #: Globally over-exposed, under-exposed & low-contrast images • Test Images include party, family, vacation, landscape, street view, pets

  4. Local exposure auto-correction • High dynamic range scene input Auto adjustment [WLPG] Local shadow / Highlight [ours]

  5. Local exposure auto-correction • Back-lighting object input Auto adjustment [WLPG] Local shadow / Highlight [ours]

  6. High dynamic range scene detection segment scene region sky region input extract features sky detection , , local contrast in scene region sky histogram scene histogram classifier confidence map of sky

  7. Samples of high dynamic range scene • False: • True:

  8. High dynamic range scene #: True HDR scene images / Test Images

  9. Back-lighting object detection • The most attractive backlit object is human! extract features face detection Histogram, local contrast in face/body region input classifier Histogram of image body detection input

  10. Samples of back-lighting object • False: • True:

  11. Back-lighting object #: True backlit human images / Test Images

  12. Summary • Global incorrect exposure v.s. local incorrect exposure • The “detected Human + Sky images” account for almost 66.5% of the whole test images

More Related