High dynamic range imaging by varying exposure time, gain and aperture of a video camera

To generate high dynamic range (HDR) images usually the exposure time is the only parameter varied when acquiring the low dynamic range (LDR) image series. In this paper the f-number and the gain of the camera are also considered to be variable as exposure defining parameter. This enables HDR imaging for image acquisition systems with limited exposure time range to prevent motion blur. The impacts of the added parameters gain and f-number are analyzed. Since common HDR image generating algorithms require the exposure time as input, an approach to estimate an equivalent exposure time by the used parameter set (exposure time, f-number and camera gain) is shown. Further this equivalent exposure time can also be estimated without a priori knowledge of the parameter set. At the end of the paper a quality assurance application is shown, where this extended parameter set was used and proved necessary for the HDR image acquisition.

[1]  Murali Subbarao,et al.  Depth from defocus by changing camera aperture: a spatial domain approach , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[2]  Greg Ward,et al.  Fast, Robust Image Registration for Compositing High Dynamic Range Photographs from Hand-Held Exposures , 2003, J. Graphics, GPU, & Game Tools.

[3]  Steve Mann,et al.  ON BEING `UNDIGITAL' WITH DIGITAL CAMERAS: EXTENDING DYNAMIC RANGE BY COMBINING DIFFERENTLY EXPOSED PICTURES , 1995 .

[4]  Jitendra Malik,et al.  Recovering high dynamic range radiance maps from photographs , 1997, SIGGRAPH.

[5]  Michael Guthe,et al.  Freehand HDR photography with motion compensation , 2007, VMV.

[6]  Akihiro Horii Depth from Defocusing , 1992 .

[7]  Shree K. Nayar,et al.  Determining the Camera Response from Images: What Is Knowable? , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Steven A. Shafer,et al.  Depth from focusing and defocusing , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[9]  G. Richardson Keep the noise down , 1993, Current Biology.

[10]  W. Zinth,et al.  Optik: Lichtstrahlen - Wellen - Photonen , 2008 .

[11]  Robert L. Stevenson,et al.  Dynamic range improvement through multiple exposures , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[12]  Anna Tomaszewska,et al.  Image Registration for Multi-exposure High Dynamic Range Image Acquisition , 2007 .

[13]  M. Pollefeys,et al.  Radiometric Self-Alignment of Image Sequences ( CVPR ’ 04 ) , 2004 .

[14]  J. Mixter Fast , 2012 .

[15]  Shree K. Nayar,et al.  Radiometric self calibration , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).