A fast multi-scale decomposition based tone mapping algorithm for High Dynamic Range images

Traditional digital display devices, due to their hardware limitations, cannot represent the whole range of luminance in High Dynamic Range (HDR) images. In order to solve this incompatible problem, many tone mapping techniques were introduced to reproduce HDR images presently. Unlike one of the traditional work of art in [13], this paper proposes a fast and multi-scale decomposition based tone mapping algorithm using the Improved Local Extrema (ILE) filter depended on the correlation of pixels. The reason of using ILE filter is due to the fact that it is able to decrease the time-consuming without noticeable image quality deterioration. Firstly, the ILE filters of variant scales are utilized to dispose the input HDR image into a series of base images under different scales. Secondly, multi-scale decomposition is utilized to obtain detail images with variable scales from the aforementioned base images. Finally, both of the base and detail images are converted into an initial compressed image to generate a Low Dynamic Range (LDR) image. Experimental results show that the proposed algorithm outperforms previous methods for reconstructing the real scene of HDR images, especially for its fast running time compared with the traditional work using Local Extrema (LE) filter.

[1]  Peipei Zhou,et al.  HDR imaging based on region segmentation , 2015, The 27th Chinese Control and Decision Conference (2015 CCDC).

[2]  Dani Lischinski,et al.  Colorization using optimization , 2004, SIGGRAPH 2004.

[3]  Dani Lischinski,et al.  Colorization using optimization , 2004, ACM Trans. Graph..

[4]  N. Huang,et al.  The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[5]  E. Reinhard Photographic Tone Reproduction for Digital Images , 2002 .

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

[7]  Mark D. Fairchild,et al.  iCAM06: A refined image appearance model for HDR image rendering , 2007, J. Vis. Commun. Image Represent..

[8]  Jan Kautz,et al.  Local Laplacian filters: edge-aware image processing with a Laplacian pyramid , 2011, SIGGRAPH 2011.

[9]  Michael Elad,et al.  Retinex by Two Bilateral Filters , 2005, Scale-Space.

[10]  Chang Liu,et al.  Affine invariant features-based tone mapping algorithm for high dynamic range images , 2014, 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[11]  Frédo Durand,et al.  Edge-preserving multiscale image decomposition based on local extrema , 2009, ACM Trans. Graph..

[12]  Kurt Debattista,et al.  A framework for inverse tone mapping , 2007, The Visual Computer.

[13]  Wolfgang Heidrich,et al.  Color correction for tone mapping , 2009, Comput. Graph. Forum.

[14]  Manuel M. Oliveira,et al.  Domain transform for edge-aware image and video processing , 2011, SIGGRAPH 2011.

[15]  T. Lindeberg,et al.  Scale-Space Theory : A Basic Tool for Analysing Structures at Different Scales , 1994 .

[16]  Zhou Wang,et al.  Objective Quality Assessment of Tone-Mapped Images , 2013, IEEE Transactions on Image Processing.

[17]  Erik Reinhard,et al.  Progressive color transfer for images of arbitrary dynamic range , 2011, Comput. Graph..

[18]  Giovanni Ramponi,et al.  High Dynamic Range Image Display With Halo and Clipping Prevention , 2011, IEEE Transactions on Image Processing.

[19]  Zeev Farbman,et al.  Edge-preserving decompositions for multi-scale tone and detail manipulation , 2008, SIGGRAPH 2008.