计算机应用 ›› 2016, Vol. 36 ›› Issue (4): 1115-1119.DOI: 10.11772/j.issn.1001-9081.2016.04.1115

• 虚拟现实与数字媒体 • 上一篇    下一篇

基于先验置信传播的图像修复改进算法

王佳君, 喻强, 张晶晶   

  1. 西南交通大学 信息科学与技术学院, 成都 610031
  • 收稿日期:2015-09-10 修回日期:2015-10-22 出版日期:2016-04-10 发布日期:2016-04-08
  • 通讯作者: 王佳君
  • 作者简介:王佳君(1990-),男,河北藁城人,硕士研究生,主要研究方向:数字图像处理; 喻强(1991-),男,湖北武汉人,硕士研究生,主要研究方向:数字图像处理; 张晶晶(1991-),女,湖北随州人,硕士研究生,主要研究方向:数字图像处理。
  • 基金资助:
    国家自然科学基金资助项目(61461048);国家社会科学基金资助项目(12EF19);西藏自治区重点科技计划项目(Z2013B28G28/02);国家级大学生创新创业训练计划项目(201210694019)。

Improvement algorithm of image inpainting based on priority-belief propagation

WANG Jiajun, YU Qiang, ZHANG Jingjing   

  1. School of Information Science and Technology, Southwest Jiaotong University, Chengdu Sichuan 610031, China
  • Received:2015-09-10 Revised:2015-10-22 Online:2016-04-10 Published:2016-04-08
  • Supported by:
    This work is partially supported by the National Natural Science Foundation of China(61461048), the National Social Science Foundation of China(12EF19), the Emphasis Technology Plan of Tibet Autonomous Region(Z2013B28G28/02), the College Students' Innovation and Entrepreneurship Training Project (201210694019).

摘要: 先验置信传播(priority-BP)算法很难在实际中达到实时处理的要求,计算效率也有很大的提升空间。针对先验BP算法在图像修复上的应用,改进算法主要在信息传递以及标签搜索方面提出改进措施。在信息传递方面,改进的算法在初次迭代前利用图像的稀疏表示,快速更新目标区域的初始图像信息,为首次迭代提供更为准确的先验值,加速信息传递的收敛速度,并提高标签裁减和传递消息的准确度;在搜索策略方面,改进的先验BP算法舍弃了单一的全局搜索方法,在全局搜索中结合局部搜索方式,提高了标签集的组建效率。最后,将改进算法用于实例验证,待修复图像尺寸越大,改进算法优势越明显,即使在较小的图像尺寸(120×126)下,改进算法修复效果的峰值信噪比(PSNR)相对原算法平均提高了1.1 dB, 修复时间减少了接近1.2 s。实例验证结果表明该算法不但可以有效地提高图像修复的精度,而且提高了图像修复的效率。

关键词: 图像修复, 信息传递, 稀疏表示, 标签搜索, 局部搜索

Abstract: Priority Belief Propagation (priority-BP) algorithm cannot satisfy real-time requirement, and there is much room to improve its computational efficiency. As for its application in image inpainting, the main improvements of priority-BP algorithm focused on information transmission and tag searching. In information transmission step, sparse representation of image was wielded into the first iteration and the initial image information of target area was rapidly updated to provide more accurate prior information for the first iteration, which accelerated information transmission and improved the accuracy of tag trimming and information transmission. In tag searching step, the global searching was integrated with local searching instead of just only global searching so as to improve the construction efficiency of tag set. The improved algorithm was verified by examples. The results show that it has obvious advantage in inpainting images with large size; even with the small size of 120×126, it still improves the Peak Signal-to-Noise Ratio (PSNR) by 1.1 dB compared with original priority-BP algorithm, and reduces time consumption up to 1.2 seconds compared with original priority-BP algorithm. The experimental results indicate that the propsed algorithm can effectively improve the inpainting accuracy and efficiency.

Key words: image inpainting, information transmission, sparse representation, tag searching, local searching

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