Iterative colour correction of multicamera systems using corresponding feature points

  • Authors:

  • Mehrdad Panahpour Tehrani;Akio Ishikawa;Shigeyuki Sakazawa;Atsushi Koike

  • Affiliations:

  • Ultra Realistic Communications KDDI R&D Laboratories Inc., 2-1-15, Ohara, Fujimino, Saitama 356-8502, Japan and Department of Electrical Engineering and Computer Science, Graduate School of Engine ...;Ultra Realistic Communications KDDI R&D Laboratories Inc., 2-1-15, Ohara, Fujimino, Saitama 356-8502, Japan;Ultra Realistic Communications KDDI R&D Laboratories Inc., 2-1-15, Ohara, Fujimino, Saitama 356-8502, Japan;Ultra Realistic Communications KDDI R&D Laboratories Inc., 2-1-15, Ohara, Fujimino, Saitama 356-8502, Japan and Department of Computer and Information Science, Faculty of Science and Technology, S ...

  • Venue:
  • Journal of Visual Communication and Image Representation
  • Year:
  • 2010

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Abstract

Multiview images captured by multicamera systems are generally not uniform in colour domain. In this paper, we propose a novel colour correction method of multicamera systems that can (i) be applied to not only dense multicamera system, but also sparse multicamera configuration and (ii) obtain an average colour pattern among all cameras. Our proposed colour correction method starts from any camera on the array sequentially, following a certain path, for pairs of cameras, until it reaches the starting point and triggers several iterations. The iteration stops when the correction applied to the images becomes small enough. We propose to calculate the colour correction transformation based on energy minimisation using a dynamic programming of a nonlinearly weighted Gaussian-based kernel density function of geometrically corresponding feature points, obtained by the modified scale invariant feature transformation (SIFT) method, from several time instances and their Gaussian-filtered images. This approach guarantees the convergence of the iteration procedure without any visible colour distortion. The colour correction is done for each colour channel independently. The process is entirely automatic, after estimation of the parameters through the algorithm. Experimental results show that the proposed iteration-based algorithm can colour-correct the dense/sparse multicamera system. The correction is always converged with average colour intensity among viewpoint, and out-performs the conventional method.