摘要
图像复原过程中图像的主观视觉质量与图像的局部细节信息之间密切相关。针对散焦模糊图像,提出一种新的图像复原方法。所提方法在传统双边总变分正则化方法基础上,通过引入一种具有结构自适应的局部权值函数,构造了一种新的图像复原目标函数。该目标函数综合考虑了图像的全局与局部统计特性,即在整体保真情况下还充分考虑了图像的局部结构信息,使得所提复原方法能更有效地保持图像的边缘等细节信息。与传统BTV正则化方法的比较实验表明,所提方法在边缘保持方面更有效,复原后的图像具有更好的主、客观视觉质量。
Relevant research on image restoration indicates that image＇ s subjective visual quality is closely related to its local details. A novel restoration algorithm for defocus blurred image was proposed. The proposed algorithm based on BTV regularization framework by introducing a local adaptive weighted function constructs a new cost function for image restoration. This cost function which not only takes into account the global data-fidelity, but also considers the local statistical properties of image,meaning to fully consider the local structural features of image under global data-fidelity, hence behaves much better in edge preservation. Experimental results confirm the effectiveness of the proposed method. The image is restored with better subjective and objective visual quality, compared with other methods such as traditional BTV regularization approach.
出处
《计算机科学》
CSCD
北大核心
2010年第7期270-272,共3页
Computer Science
基金
福建省自然科学基金(2008J0032
2009J01301
2009J01302)
厦门大学985二期信息创新平台资助项目(0000-X07204)
厦门市科技计划高校创新项目(3502Z20083006)资助
关键词
图像复原
点扩散函数
双边总变分
局部权值函数
Image restoration, Point spread function, Bilateral total variation, Local weighted function
