Segmentation Based Tone-Mapping for High Dynamic Range Images

In this paper, we present a novel segmentation based method for displaying high dynamic range image. We segment images into regions and then carry out adaptive contrast and brightness adjustment using global tone mapping operator in the local regions to reproduce local contrast and brightness and ensure better quality. We propose a weighting scheme to eliminate the boundary artifacts caused by the segmentation and decrease the local contrast enhancement adaptively in the uniform area to eliminate the noise introduced. We demonstrate that our methods are easy to use and a fixed set of parameter values produces good results for a wide variety of images.

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

[2]  Neill W Campbell,et al.  IEEE International Conference on Computer Vision and Pattern Recognition , 2008 .

[3]  Jianbo Shi,et al.  Spectral segmentation with multiscale graph decomposition , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[4]  Graham D. Finlayson,et al.  Learning to display high dynamic range images , 2004, Pattern Recognit..

[5]  Karol Myszkowski,et al.  Adaptive Logarithmic Mapping For Displaying High Contrast Scenes , 2003, Comput. Graph. Forum.

[6]  Greg Ward,et al.  A Contrast-Based Scalefactor for Luminance Display , 1994, Graphics Gems.

[7]  Guoping Qiu,et al.  Fast tone mapping for high dynamic range images , 2004, ICPR 2004.

[8]  Edward H. Adelson,et al.  Compressing and companding high dynamic range images with subband architectures , 2005, SIGGRAPH 2005.

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

[10]  Jitendra Malik,et al.  Recovering high dynamic range radiance maps from photographs , 1997, SIGGRAPH '08.

[11]  Guillermo Sapiro,et al.  Visualization of high dynamic range images , 2003, IEEE Trans. Image Process..

[12]  Oscar C. Au,et al.  Recent advances in high dynamic range imaging technology , 2010, 2010 IEEE International Conference on Image Processing.

[13]  Mark D. Fairchild,et al.  Evaluation of HDR tone‐mapping algorithms using a high‐dynamic‐range display to emulate real scenes , 2007, CIC.

[14]  Dorin Comaniciu,et al.  Mean Shift: A Robust Approach Toward Feature Space Analysis , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  Greg Turk,et al.  LCIS: a boundary hierarchy for detail-preserving contrast reduction , 1999, SIGGRAPH.

[16]  Paul S. Heckbert,et al.  Graphics gems IV , 1994 .

[17]  Kin-Man Lam,et al.  An adaptive algorithm for the display of high-dynamic range images , 2007, J. Vis. Commun. Image Represent..

[18]  Wolfgang Heidrich,et al.  High dynamic range display systems , 2004, SIGGRAPH 2004.

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

[20]  Hiroshi Yamaguchi,et al.  Evaluating HDR rendering algorithms , 2007, TAP.

[21]  Christine D. Piatko,et al.  A Visibility Matching Tone Reproduction Operator for High Dynamic Range Scenes , 1997, IEEE Trans. Vis. Comput. Graph..

[22]  Kenneth Chiu,et al.  Spatially Nonuniform Scaling Functions for High Contrast Images , 1993 .

[23]  Hans-Peter Seidel,et al.  Analysis of Reproducing Real‐World Appearance on Displays of Varying Dynamic Range , 2006, Comput. Graph. Forum.

[24]  Allen Y. Yang,et al.  Unsupervised segmentation of natural images via lossy data compression , 2008, Comput. Vis. Image Underst..

[25]  Holly E. Rushmeier,et al.  Tone reproduction for realistic images , 1993, IEEE Computer Graphics and Applications.

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

[27]  Donald P. Greenberg,et al.  A model of visual adaptation for realistic image synthesis , 1996, SIGGRAPH.

[28]  Zia-ur Rahman,et al.  A multiscale retinex for bridging the gap between color images and the human observation of scenes , 1997, IEEE Trans. Image Process..

[29]  Guoping Qiu,et al.  Tone-mapping high dynamic range images by novel histogram adjustment , 2010, Pattern Recognit..

[30]  Erik Reinhard,et al.  Spatial Tone Reproduction , 2006 .

[31]  O. Yadid-Pecht,et al.  Wide-Dynamic-Range CMOS Image Sensors—Comparative Performance Analysis , 2009, IEEE Transactions on Electron Devices.

[32]  Zeev Farbman,et al.  Interactive local adjustment of tonal values , 2006, SIGGRAPH 2006.

[33]  Erik Reinhard,et al.  Photographic tone reproduction for digital images , 2002, ACM Trans. Graph..

[34]  De Xu,et al.  An Adaptive Tone Mapping Method for Displaying High Dynamic Range Images , 2010, J. Inf. Sci. Eng..

[35]  Michael Wimmer,et al.  Evaluation of HDR tone mapping methods using essential perceptual attributes , 2008, Comput. Graph..

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

[37]  Jitendra Malik,et al.  Learning Probabilistic Models for Contour Completion in Natural Images , 2008, International Journal of Computer Vision.

[38]  Jitendra Malik,et al.  From contours to regions: An empirical evaluation , 2009, CVPR.

[39]  Daniel P. Huttenlocher,et al.  Efficient Graph-Based Image Segmentation , 2004, International Journal of Computer Vision.

[40]  Hans-Peter Seidel,et al.  Computational model of lightness perception in high dynamic range imaging , 2006, Electronic Imaging.