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席志红, 赵蓝飞. 基于格林函数的动态范围压缩算法[J]. 计算机辅助设计与图形学学报, 2014, 26(4): 581-589.
引用本文: 席志红, 赵蓝飞. 基于格林函数的动态范围压缩算法[J]. 计算机辅助设计与图形学学报, 2014, 26(4): 581-589.
Xi Zhihong, Zhao Lanfei. Dynamic Range Compression Algorithm Based on Green’s Function[J]. Journal of Computer-Aided Design & Computer Graphics, 2014, 26(4): 581-589.
Citation: Xi Zhihong, Zhao Lanfei. Dynamic Range Compression Algorithm Based on Green’s Function[J]. Journal of Computer-Aided Design & Computer Graphics, 2014, 26(4): 581-589.

基于格林函数的动态范围压缩算法

Dynamic Range Compression Algorithm Based on Green’s Function

  • 摘要: 为了解决高动态范围图像存在的视觉效果较差以及细节不突出的缺陷,提出一种基于格林函数的动态范围压缩算法.该算法通过稀疏表示将图像分割为多个亮度差异较大的不规则区域;并通过计算各区域的地球移动距离匹配出阴影与高光区域的相似区域;最后提出一种构造不规则区域格林函数的数值解法,结合边界条件,通过曲线积分得到适于显示的低动态范围图像.实验结果表明,稀疏表示抑制了由曲线积分产生的累积误差,数值解法在压缩动态范围的同时有效地增强了图像的细节信息,生成的图像视觉效果较好,清晰度较高.

     

    Abstract: Due to the uncomfortable visual effect and unclearly details which exist in high dynamic range images, this paper proposes a dynamic range compression algorithm based on Green's function. This algorithm employs the sparse representation method to obtain irregular regions which possess wide disparity in term of luminance.The similar regions of shadow and highlight domains are retrieved by calculating of the earth mover distance between regions.A numerical solution for irregular regions is introduced to calculate low dynamic range images which are derived from the curvilinear integral according to the Dirichlet boundary condition. Experimental results show that the sparse representation method restrains the accumulative errors which are caused by curvilinear integral.The numerical solution enhances the image details efficiently, meanwhile the dynamic range is compressed. The resulting images represent excellent effect of sense and high clarity.

     

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