Using Spatially Varying Pixels Exposures and Bayer-covered Photosensors for High Dynamic Range Imaging

The method of a linear high dynamic range imaging using solid-state photosensors with Bayer colour filters array is provided in this paper. Using information from neighbour pixels, it is possible to reconstruct linear images with wide dynamic range from the oversaturated images. Bayer colour filters array is considered as an array of neutral filters in a quasimonochromatic light. If the camera's response function to the desirable light source is known then one can calculate correction coefficients to reconstruct oversaturated images. Reconstructed images are linearized in order to provide a linear high dynamic range images for optical-digital imaging systems. The calibration procedure for obtaining the camera's response function to the desired light source is described. Experimental results of the reconstruction of the images from the oversaturated images are presented for red, green, and blue quasimonochromatic light sources. Quantitative analysis of the accuracy of the reconstructed images is provided.

[1]  Shree K. Nayar,et al.  Adaptive dynamic range imaging: optical control of pixel exposures over space and time , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[2]  Narendra Ahuja,et al.  Split Aperture Imaging for High Dynamic Range , 2004, International Journal of Computer Vision.

[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 '08.

[5]  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).

[6]  Vladislav G. Rodin,et al.  Input scene restoration in pattern recognition correlator based on digital photo camera , 2007, SPIE Defense + Commercial Sensing.

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

[8]  B.J. Hosticka,et al.  A high dynamic range CMOS image sensor for automotive applications , 2000, Proceedings of the 25th European Solid-State Circuits Conference.

[9]  Edward R. Dowski,et al.  A New Paradigm for Imaging Systems , 2002, PICS.

[10]  Richard H. Byrd,et al.  Approximate solution of the trust region problem by minimization over two-dimensional subspaces , 1988, Math. Program..

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

[12]  Jorge J. Moré,et al.  Computing a Trust Region Step , 1983 .

[13]  Shree K. Nayar,et al.  Enhancing resolution along multiple imaging dimensions using assorted pixels , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.