摘要
提出一种基于各向异性热扩散方程的散焦图像深度恢复算法。利用各向异性热扩散建模散焦成像过程,将散焦图像深度恢复转化为带有整体变分正则化项的能量泛函极值问题,通过迭代获得景物的深度信息。该算法不需要恢复聚焦图像,并且未施加额外的约束条件。模拟和真实图像实验结果表明,该算法有效,且深度恢复效果优于最小二乘法。
A novel algorithm for recovering depth of objects from defocus images is presented, based on the anisotropic heat diffusion model. The defocus process is modeled using the model of anisotropic heat diffusion. The depth recovery, problem is converted into the energy functional minimum problem with a regularization term of total variation. The depth information of the object is obtained by iterative procedures. The algorithm avoids recovering a focus image and exerting excess restrictions. Experimental results show that the algorithm is valid with small error.
出处
《计算机工程》
CAS
CSCD
北大核心
2010年第18期169-170,173,共3页
Computer Engineering
基金
国家自然科学基金资助项目(60872106
60603083)
关键词
深度信息
散焦图像
各向异性热扩散
整体变分
depth information
defocus image
anisotropic beat diffusion
total variation
