5 August 2015 The L_infinity constrained global optimal histogram equalization technique for real time imaging
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Abstract
Although the current imaging sensors can achieve 12 or higher precision, the current display devices and the commonly used digital image formats are still only 8 bits. This mismatch causes significant waste of the sensor precision and loss of information when storing and displaying the images. For better usage of the precision-budget, tone mapping operators have to be used to map the high-precision data into low-precision digital images adaptively. In this paper, the classic histogram equalization tone mapping operator is reexamined in the sense of optimization. We point out that the traditional histogram equalization technique and its variants are fundamentally improper by suffering from local optimum problems. To overcome this drawback, we remodel the histogram equalization tone mapping task based on graphic theory which achieves the global optimal solutions. Another advantage of the graphic-based modeling is that the tone-continuity is also modeled as a vital constraint in our approach which suppress the annoying boundary artifacts of the traditional approaches. In addition, we propose a novel dynamic programming technique to solve the histogram equalization problem in real time. Experimental results shows that the proposed tone-preserved global optimal histogram equalization technique outperforms the traditional approaches by exhibiting more subtle details in the foreground while preserving the smoothness of the background.
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Qiongwei Ren, Qiongwei Ren, Yi Niu, Yi Niu, Lin Liu, Lin Liu, Yang Jiao, Yang Jiao, Guangming Shi, Guangming Shi, } "The L_infinity constrained global optimal histogram equalization technique for real time imaging", Proc. SPIE 9622, 2015 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, 962206 (5 August 2015); doi: 10.1117/12.2193251; https://doi.org/10.1117/12.2193251
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