Key points identification in the HDR-images

Author(s) Collection number Pages Download abstract Download full text
Pylyp’yuk V. V., Tsimer O. B. № 2 (51) 41-45 Image Image

The issue of identifying key points in the HDR-images has been analyzed. The issue includes image recognition, the panoramic parts of which should be connected. The method for creating of the panoramic images from the consecutively created HDR-images has been proposed. The advantage of this method is providing the highest level of quality of the panorama received. The SIFT algorithm features to determine the relevant items have been considered. Based on the algorithm the local image characteristics have been described and identified.

Keywords: key point, dynamic range, HDR-image, SIFT algorithm, local features, difference of Gaussian.


  • 1. HDRSOFT: Technical report (2005), available at: http://www.hdrsoft.com/examples.html.
  • 2. Brown M. (2003), Recognizing Panoramas, Proceedings of the Ninth IEEE International Conference on Computers. Vision (ICCV’03), Vol. 2.
  • 3. David G. Lowe (2004), Distinctive Image Features from Scale-Invariant Key points, University of British Columbia press, Vancouver.
  • 4. Brown M. (2004), Recognizing Panoramas in slides, University of British Columbia press, Vancouver.
  • 5. Burt J. (1983), A Multiresolution Spline with Application to Image Mosaics, RCA David Sarnoff Research Center.
  • 6. Greg Ward. (2001), High Dynamic Range Imaging. Exponent Failure Analysis, Associations.