Non-parametric estimation of camera function

In this paper a non-parametric, direct estimation of camera response function is presented and evaluated in real and simulated data, using multiple images of an arbitrary scene acquired in different exposure times. Initially, it is proved that the subtraction of the logarithm of the inverse response function of any pair of pixels is invariant to the integration time and equal to the logarithm of the ratio of the camera responses. Based on this property, the proposed method estimates the response function in a non-iterative manner, solving an appropriately set linear system of equations. The direct solution, evaluated under a representative set of experiments, shows that even in the case of unknown exposure times, the mean absolute error of the camera's estimated response function is lower than 0.020 in all simulation experiments and 0.018, 0.021, and 0.023 for the RGB channels of the Olympus 5050Zoom digital camera

[1]  E. Land,et al.  Lightness and retinex theory. , 1971, Journal of the Optical Society of America.

[2]  Richard Szeliski,et al.  Image mosaicing for tele-reality applications , 1994, Proceedings of 1994 IEEE Workshop on Applications of Computer Vision.

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

[4]  Frank M. Candocia,et al.  A semiparametric model for accurate camera response function modeling and exposure estimation from comparametric data , 2005, IEEE Transactions on Image Processing.

[5]  S. Mann,et al.  Steps towards 'undigital' intelligent image processing: real-valued image coding of photoquantimetric pictures into the JLM file format for the compression of portable lightspace maps , 2004, Proceedings of 2004 International Symposium on Intelligent Signal Processing and Communication Systems, 2004. ISPACS 2004..

[6]  Ping-Sing Tsai,et al.  Shape from Shading: A Survey , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Stephen Westland,et al.  Accurate Estimation of the Non-Linearity of Input-Output Response for Color Digital Cameras , 2003, PICS.

[8]  M. Pollefeys,et al.  Radiometric alignment of image sequences , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[9]  Hans-Peter Seidel,et al.  Perception-motivated high dynamic range video encoding , 2004, SIGGRAPH 2004.

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

[11]  Robert J. Woodham,et al.  Reflectance map techniques for analyzing surface defects in metal castings , 1978 .

[12]  Dani Lischinski,et al.  Gradient Domain High Dynamic Range Compression , 2023 .

[13]  Marc Pollefeys,et al.  Radiometric alignment of image sequences , 2004, CVPR 2004.

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

[15]  Steve Mann,et al.  Quantigraphic Imaging: Estimating the camera response and exposures from differently exposed images , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[16]  Frank M. Candocia,et al.  Analysis and enhancements to piecewise linear comparametric image registration , 2005, IEEE Transactions on Image Processing.

[17]  Mubarak Shah,et al.  Estimation of the radiometric response functions of a color camera from differently illuminated images , 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

[18]  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.

[19]  Luís Paulo Santos,et al.  A local model of eye adaptation for high dynamic range images , 2004, AFRIGRAPH '04.

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