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计算机工程 ›› 2010, Vol. 36 ›› Issue (10): 187-189. doi: 10.3969/j.issn.1000-3428.2010.10.064

• 图形图像处理 • 上一篇    下一篇

基于图像分解的图像修复技术

林云莉1, 赵俊红1, 朱学峰1, 胡永健2   

  1. (1. 华南理工大学自动化科学与工程学院,广州 510640;2. 华南理工大学电子与信息学院,广州 510640)
  • 出版日期:2010-05-20 发布日期:2010-05-20

Image Inpainting Technology Based on Image Decomposition

LIN Yun-li1, ZHAO Jun-hong1, ZHU Xue-feng1, HU Yong-jian2   

  1. (1. College of Automation Science and Engineering, South China University of Technology, Guangzhou 510640;2. School of Electronic and Information, South China University of Technology, Guangzhou 510640)
  • Online:2010-05-20 Published:2010-05-20

摘要:

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。

关键词: 图像修复, 整体变分模型, 图像分解, 结构信息, 纹理信息

Abstract:

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.

Key words: image inpainting, Total Variation(TV) model, image decomposition, structure information, texture information

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