本文探讨了一种利用结构约束和样本稀疏表示,对结构信息缺损较大时的图像修复方法。利用多项式曲线拟合方式修复图像边缘信息,约束结构的修复;采用样本稀疏表示的窄带模型,优先修复结构信息;利用平移块的稀疏表示方法修复纹理信息。仿真实验结果表明,该方法修复图像质量高,既可较好地修复图像的边缘结构,又能保持结构的整体平滑性。

In this paper, we discuss a way of image inpainting with large defect of structural information by structural constraints and sample sparse representations. The image edge information is repaired by a polynomial curve fitting to constrain the structural information. First, a narrow-band model of sample sparse representation is used to repair structural information. Then, the texture information is completed by a translational block sparse representation method. Simulation results show that proposed method can achieve higher image quality, and can better repair the structure information and maintain the smoothness of structure integrally.