A wavelet coefficients based dynamic range compression technique for infrared images

14-bit or 16-bit pixel depth high dynamic-range images are acquired from visible band cameras and from infrared imaging devices which are more widely used nowadays. Usually, linear mapping is used to display these images to operators. However, results of the researches done to map images into 0-255 range in recent years show that different techniques result in major differences at image perception and detail visibility. Successful compression of image dynamic range increases the operator awareness for surveillance systems and ensure more effective display of scene details to user. Besides, dynamic-range compression techniques effect the enhancement of the success rate of image target detection and tracking techniques. In this work, scene components are analyzed using wavelet coefficients and intensity distribution of scene components are extracted. Extracted intensity distribution is used to display scene components effectively.

[1]  Karel J. Zuiderveld,et al.  Contrast Limited Adaptive Histogram Equalization , 1994, Graphics Gems.

[2]  Marco Diani,et al.  New technique for the visualization of high dynamic range infrared images , 2009 .

[3]  Jean-Charles Pinoli,et al.  Image dynamic range enhancement and stabilization in the context of the logarithmic image processing model , 1995, Signal Process..

[4]  John J. McCann,et al.  Retinex in Matlab , 2000, CIC.

[5]  S. Laughlin A Simple Coding Procedure Enhances a Neuron's Information Capacity , 1981, Zeitschrift fur Naturforschung. Section C, Biosciences.

[6]  Sung-Jea Ko,et al.  Novel contrast enhancement scheme for infrared image using detail-preserving stretching , 2011 .

[7]  Tayfun Aytaç,et al.  Adaptive enhancement of sea-surface targets in infrared images based on local frequency cues. , 2010, Journal of the Optical Society of America. A, Optics, image science, and vision.

[8]  Vijayan K. Asari,et al.  An automatic wavelet-based nonlinear image enhancement technique for aerial imagery , 2009, 2009 4th International Conference on Recent Advances in Space Technologies.

[9]  B. Potocnik,et al.  Image enhancement by using directional wavelet transform , 2006, 28th International Conference on Information Technology Interfaces, 2006..

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

[11]  Tayfun Aytac,et al.  Adaptive image enhancement based on clustering of wavelet coefficients for infrared sea surveillance systems , 2011 .