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Adaptive image contrast enhancement algorithm for point-based rendering

[+] Author Affiliations
Shaoping Xu

NangChang University, School of Information Engineering, Department of Computer Science and Technology, XueFu Road #999, NangChang 330031, JiangXi Province, China

Xiaoping P. Liu

NangChang University, School of Information Engineering, Department of Computer Science and Technology, XueFu Road #999, NangChang 330031, JiangXi Province, China

Carleton University, Department of Systems and Computer Engineering, Ottawa K1S 5B6, Ontario, Canada

J. Electron. Imaging. 24(2), 023033 (Apr 23, 2015). doi:10.1117/1.JEI.24.2.023033
History: Received October 12, 2014; Accepted March 24, 2015
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Abstract.  Surgical simulation is a major application in computer graphics and virtual reality, and most of the existing work indicates that interactive real-time cutting simulation of soft tissue is a fundamental but challenging research problem in virtual surgery simulation systems. More specifically, it is difficult to achieve a fast enough graphic update rate (at least 30 Hz) on commodity PC hardware by utilizing traditional triangle-based rendering algorithms. In recent years, point-based rendering (PBR) has been shown to offer the potential to outperform the traditional triangle-based rendering in speed when it is applied to highly complex soft tissue cutting models. Nevertheless, the PBR algorithms are still limited in visual quality due to inherent contrast distortion. We propose an adaptive image contrast enhancement algorithm as a postprocessing module for PBR, providing high visual rendering quality as well as acceptable rendering efficiency. Our approach is based on a perceptible image quality technique with automatic parameter selection, resulting in a visual quality comparable to existing conventional PBR algorithms. Experimental results show that our adaptive image contrast enhancement algorithm produces encouraging results both visually and numerically compared to representative algorithms, and experiments conducted on the latest hardware demonstrate that the proposed PBR framework with the postprocessing module is superior to the conventional PBR algorithm and that the proposed contrast enhancement algorithm can be utilized in (or compatible with) various variants of the conventional PBR algorithm.

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Citation

Shaoping Xu and Xiaoping P. Liu
"Adaptive image contrast enhancement algorithm for point-based rendering", J. Electron. Imaging. 24(2), 023033 (Apr 23, 2015). ; http://dx.doi.org/10.1117/1.JEI.24.2.023033


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