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HDR Imaging

TNT members involved in this project:
Hanno Ackermann, Ph.D.
Dipl.-Ing. Holger Meuel
Prof. Dr.-Ing. Jörn Ostermann
Prof. Dr.-Ing. Bodo Rosenhahn

We aim at simplified high dynamic range (HDR) image generation with non-modified, conventional camera sensors. One typical HDR approach is exposure bracketing, e. g. with varying shutter speeds. It requires to capture the same scene multiple times at different exposure times. These pictures are then merged into a single HDR picture which typically is converted back to an 8-bit image by using tone-mapping.


Existing works on HDR imaging focus on image merging and tone mapping whereas we aim at simplified image acquisition. The proposed algorithm can be used in consumer-level cameras without hardware modifications at sensor level. Based on intermediate samplings of each sensor element during the total (pre-defined)
exposure time, we extrapolate the luminance of sensor elements which are saturated after the total exposure time. Compared to existing HDR approaches which typically require three different images with carefully determined exposure times, we only take one image at the longest exposure time. The shortened total
time between start and end of image acquisition can reduce ghosting artifacts.

Idea: Sample intermediate values during exposure without reset

  • Consider only pels below saturation for each sampling step
  • Pel-wise temporal extrapolation
  • Pel-wise averaging of temporally extrapolated pels

Improvement for noise reduction:

  • Weighted averaging of temporally extrapolated samples
Sampling during exposure scheme
Sampling during exposure scheme (shown: noise-free case)

 

Total acquisition time t E << t total,common ⇒ ghosting artifacts less likely to occur 

Matlab vs. proposed
Upper left: common MATLAB-HDR (v. 2016b), upper right:proposed with weighted averaging
lower row: magnifications (colors match colors in upper row)

 

  • Simple HDR image generation with conventional senors
  • No or only small hardware changes required ⇒ applicable for low-cost sensors (e. g. in smartphones)
  • Reduced image noise for low-light scenarios
  • Improved detail preservation
  • Reduced total image-aquisition time ⇒ reduced ghosting

  • Conference Contributions
    • Holger Meuel, Hanno Ackermann, Bodo Rosenhahn, Jörn Ostermann
      Physical High Dynamic Range (HDR) Imaging with Conventional Sensors
      Picture Coding Symposium (PCS), June 2018