基于图像分解的图像修复技术

针对整体变分(TV)图像修复模型缺点，提出基于图像分解的修复模型。采用图像分解技术，提取图像的结构信息和纹理信息。将图像结构部分用基于TV的改进模型进行修复，避免TV模型在平滑区域产生阶梯效应。在迭代过程中，对图像的特征点与非特征点分别考虑，确保在修复过程中特征点不被模糊化，图像纹理部分采用改进的基于样本修复技术。Matlab仿真实验结果表明，改进算法的修复效果和峰值信噪比计算结果优于原始算法。

Image Inpainting Technology Based on Image Decomposition

Aiming at the drawbacks of Total Variation(TV) model for image impainting, this paper proposes an improved inpainting model based on image decomposition. Using image decomposition technology, it extracts the structure information and texture information from the image. The improved TV model is applied to structure part of image to effectively avoid step effect in TV model on smooth region. On the process of iterative, it respectively analyzes the feature points and non-feature points to avoid the fuzziness of feature points during the inpainting. Image texture information uses improved exemplar-based inpainting technology. Matlab simulation experimental results show that the inpainting effect and the results of peak signal to noise ratio are better than that of original algorithm.