Color Image Processing Pipeline in Digital Still Cameras

Digital Still Color Cameras have gained significant popularity in recent years, with projected sales in the order of 44 million units by the year 2005. Such an explosive demand calls for an understanding of the processing involved and the implementation issues, bearing in mind the otherwise difficult problems these cameras solve. This article presents an overview of the image processing pipeline, first from a signal processing perspective and later from an implementation perspective, along with the trade-offs involved.

[1]  Shree K. Nayar,et al.  High dynamic range imaging: spatially varying pixel exposures , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[2]  R. Bala,et al.  System optimization in digital color imaging , 2005, IEEE Signal Processing Magazine.

[3]  Nasser Kehtarnavaz,et al.  Color filter array interpolation using color correlations and directional derivatives , 2003, J. Electronic Imaging.

[4]  Mark S. Drew,et al.  Constrained least-squares regression in color spaces , 1997, J. Electronic Imaging.

[5]  Kevin E. Spaulding,et al.  Reference Input/Output Medium Metric RGB Color Encoding (RIMM/ROMM RGB) , 2000, PICS.

[6]  Yücel Altunbasak,et al.  Color plane interpolation using alternating projections , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[7]  J. Greivenkamp.  Color dependent optical prefilter for the suppression of aliasing artifacts. , 1990, Applied optics.

[8]  Kevin E. Spaulding,et al.  Color processing in digital cameras , 1998, IEEE Micro.

[9]  Wesley E. Snyder,et al.  Adaptive demosaicking , 2003, J. Electronic Imaging.

[10]  H. Joel Trussell,et al.  Mathematics for demosaicking , 2002, IEEE Trans. Image Process..

[11]  Muralidhara Subbarao,et al.  Selecting the Optimal Focus Measure for Autofocusing and Depth-From-Focus , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  Richard Szeliski,et al.  High dynamic range video , 2003, ACM Trans. Graph..

[13]  Yong-Moo Kwon,et al.  Implementation of a passive automatic focusing algorithm for digital still camera , 1995 .

[14]  Paul M. Hubel,et al.  Eyeing the Camera: into the Next Century , 2002, Color Imaging Conference.

[15]  K. Kikuchi,et al.  Video camera system using fuzzy logic , 1992 .

[16]  Atsushi Fujioka,et al.  A digital video camera system , 1990 .

[17]  Jack M. Holm.  Issues Relating to the Transformation of Sensor Data into Standard Color Spaces , 1997, Color Imaging Conference.

[18]  N. Kehtarnavaz,et al.  Development and Real-Time Implementation of Auto White Balancing Scoring Algorithm , 2002, Real Time Imaging.

[19]  Ken Parulski,et al.  Color image processing for digital cameras , 2002 .

[20]  J. Cohen,et al.  Color Science: Concepts and Methods, Quantitative Data and Formulas , 1968 .

[21]  Ingeborg Tastl,et al.  Gamut Constrained Illuminant Estimation , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[22]  Gaurav Sharma,et al.  Digital color imaging , 1997, IEEE Trans. Image Process..

[23]  Mark S. Drew,et al.  Matrix Calculations for Digital Photography , 1997, Color Imaging Conference.

[24]  Ron Kimmel,et al.  Demosaicing: Image Reconstruction from Color CCD Samples , 1998, ECCV.

[25]  Greg Ward,et al.  High dynamic range imaging , 2001, SIGGRAPH '04.

[26]  John P. Rossi,et al.  Digital Techniques for Reducing Television Noise , 1978 .

[27]  Brian V. Funt,et al.  A comparison of computational color constancy algorithms. I: Methodology and experiments with synthesized data , 2002, IEEE Trans. Image Process..

[28]  Sabine Süsstrunk,et al.  Standard RGB Color Spaces , 1999, CIC.

[29]  Mark S. Drew,et al.  White-point preserving color correction , 1997, Color Imaging Conference.