New technique for the visualization of high dynamic range infrared images

We propose a new dynamic range compression technique for infrared (IR) imaging systems that enhances details visibility and allows the control and adjustment of the image appearance by setting a number of tunable parameters. This technique adopts a bilateral filter to extract a details component and a coarse component. The two components are processed independently and then recombined to obtain the output-enhanced image that fits the display dynamic range. The contribution made is threefold. We propose a new technique for the visualization of high dynamic range (HDR) images that is specifically tailored to IR images. We show the effectiveness of the method by analyzing experimental IR images that represent typical area surveillance and object recognition applications. Last, we quantitatively assess the performance of the proposed technique, comparing the quality of the enhanced image with that obtained through two well-established visualization methods.

[1]  Hiroaki Kotera,et al.  Dynamic range compression preserving local image contrast for digital video camera , 2005, IEEE Transactions on Consumer Electronics.

[2]  Curtis M. Webb,et al.  Scene-based algorithm for improved FLIR performance , 2000, Defense, Security, and Sensing.

[3]  Frédo Durand,et al.  A Fast Approximation of the Bilateral Filter Using a Signal Processing Approach , 2006, International Journal of Computer Vision.

[4]  Roberto Manduchi,et al.  Bilateral filtering for gray and color images , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

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

[6]  John J. McCann,et al.  Retinex in MATLABTM , 2004, J. Electronic Imaging.

[7]  Kate Devlin,et al.  A review of tone reproduction techniques , 2002 .

[8]  Werner Purgathofer,et al.  Tone Reproduction and Physically Based Spectral Rendering , 2002, Eurographics.

[9]  Frédo Durand,et al.  Two-scale tone management for photographic look , 2006, SIGGRAPH 2006.

[10]  Danny Barash,et al.  A Fundamental Relationship between Bilateral Filtering, Adaptive Smoothing, and the Nonlinear Diffusion Equation , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Alessandro Rizzi,et al.  Random Spray Retinex: A New Retinex Implementation to Investigate the Local Properties of the Model , 2007, IEEE Transactions on Image Processing.

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

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

[14]  Tayfun Aytac,et al.  A comparison of different infrared image enhancement techniques for sea surface targets , 2009, 2009 IEEE 17th Signal Processing and Communications Applications Conference.

[15]  Robert Sobol,et al.  Improving the Retinex algorithm for rendering wide dynamic range photographs , 2002, IS&T/SPIE Electronic Imaging.

[16]  Marco Diani,et al.  Dynamic-range compression and contrast enhancement in infrared imaging systems , 2008 .