Image Decomposition Using Nonconvex Functional

摘要：

This paper proposes a new model for image decomposition by nonconvex functional minimization. Instead of using the Banach norm as the fidelity term, we use the integral of the square of residual component divided by its gradient as the fidelity term. This nonconves fidelity term has very low value for the texture image and high value for the geometric image, so it is appropriate for image decomposition. The gradient descent procedure is used to solve the proposed minimization problem, which leads to evolve a new nonlinear second-order partial differential equation to steady state. The experimental results demonstrate the proposed model makes visual improvements compared with the classical OSV model, which includes that the cartoon component has less texture and the texture component has less cartoon information.

关键词： image decomposition total variation minimization functional minimization nonconvex functional

作者: Jian Bai Xiang-Chu Feng

作者单位: dept. of mathematics Xidian University Xian, China

会议类型: 国际会议

会议名称: 2011 4th International Congress on Image and Signal Processing(第四届图像与信号处理国际学术会议 CISP 2011)

会议地点: 上海

会议语种:英文

页码: 704-707

在线出版日期: 2011-10-15（万方平台首次上网日期，不代表论文的发表时间）