@InProceedings{Cerman-CVWW06,
  IS = { zkontrolovano 29 Dec 2006 },
  UPDATE  = { 2006-09-03 },
  booktitle = { CVWW'06: Proceedings of the Computer Vision Winter Workshop 2006 },
  editor    = { Ond{\v r}ej Chum and Vojt{\v e}ch Franc },
  publisher = { Czech Society for Cybernetics and Informatics },
  address   = { Prague, Czech Republic },
  isbn      = { 80-239-6530-1 },
  book_pages = { 124 },
  title     = { Exposure time estimation for high dynamic range imaging with hand held camera },
  author    = { Cerman, Luk{\'a}{\v s} and Hlav{\'a}{\v c}, V{\'a}clav },
  pages     = { 76--81 },
  year      = { 2006 },
  month     = { February },
  day       = { 6--8 },
  venue     = { Tel{\v c}, Czech Republic },
  project   = { INTAS 04-77-7347, 1M0567, BeNoGo IST-2001-39184 },
  keywords  = { HDR, high dynamic range images, exposure time estimation },
  annote    = { The limited dynamic range of a camera may be extended by
    composing differently exposed images of the same scene. The nonlinear
    camera has to be calibrated radiometrically first. We show that the
    calibration process can be difficult for real cameras. The improvement can
    be achieved if linear 12-bit RAW images are used as offered by modern
    mid-class and professional cameras. The knowledge of exposure time
    positively affects the radiometric quality of the composed high dynamic
    range (HDR) image. This knowledge also helps in registration of differently
    exposed hand held shots.  This contribution presents a new method for
    estimating exposure times from the histograms of images captured using a
    linear response camera or generated from a RAW image.  The presented method
    does not require spatially aligned images. The actual process of HDR image
    composition needs perfectly aligned images on its input.  We present a
    method for registering differently exposed images captured with a hand held
    camera. The presented registration method enables capture of HDR images
    without the need of mounting a camera on the tripod. The methods are
    implemented in Matlab and tested on real data. },
}