Department of Electrical Engineering, Korea University, Seoul, Korea.
IEEE Trans Image Process. 2012 Mar;21(3):1191-9. doi: 10.1109/TIP.2011.2167346. Epub 2011 Sep 8.
In this paper, we propose a new sharpness enhancement algorithm for stereo images. Although the stereo image and its applications are becoming increasingly prevalent, there has been very limited research on specialized image enhancement solutions for stereo images. Recently, a binocular just-noticeable-difference (BJND) model that describes the sensitivity of the human visual system to luminance changes in stereo images has been presented. We introduce a novel application of the BJND model for the sharpness enhancement of stereo images. To this end, an overenhancement problem in the sharpness enhancement of stereo images is newly addressed, and an efficient solution for reducing the overenhancement is proposed. The solution is found within an optimization framework with additional constraint terms to suppress the unnecessary increase in luminance values. In addition, the reliability of the BJND model is taken into account by estimating the accuracy of stereo matching. Experimental results demonstrate that the proposed algorithm can provide sharpness-enhanced stereo images without producing excessive distortion.
在本文中，我们提出了一种新的立体图像锐化增强算法。尽管立体图像及其应用变得越来越普及，但针对立体图像的专门图像增强解决方案的研究却非常有限。最近，提出了一种描述人眼对立体图像中亮度变化敏感度的双目刚可察觉差（BJND）模型。我们将 BJND 模型应用于立体图像的锐化增强中。为此，我们新解决了立体图像锐化增强中的过增强问题，并提出了一种有效的解决方案来减少过增强。该解决方案是在一个带有附加约束项的优化框架内找到的，以抑制不必要的亮度值增加。此外，通过估计立体匹配的准确性，考虑了 BJND 模型的可靠性。实验结果表明，所提出的算法可以在不产生过度失真的情况下提供锐化增强的立体图像。
