计算机科学 ›› 2010, Vol. 37 ›› Issue (12): 234-237.

• 图形图像 • 上一篇    下一篇

多信道图像盲复原算法

肖宿,韩国强,沃焱   

  1. (华南理工大学计算机科学与工程学院 广州510006)
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家自然科学基金(60073079),国家支撑计划项目(X2JSB1080010)资助。

Multichannel Blind Image Restoration

XIAO Su,HAN Guo-qiang,WO Yan   

  • Online:2018-12-01 Published:2018-12-01

摘要: 为充分利用观测图像中的信息及信息之间的互补性,提高图像复原的质量,提出了贝叶斯框架下的多信道图像盲复原算法。首先,建立原始图像、点扩散函数和观测图像的先验模型,由先验模型得到原始图像、点扩散函数和观测图像的先验概率;然后用伽马分布描述未知的模型参数;最后基于最大后验概率的推导,利用实证分析法估计原始图像和点扩散函数的最优值。实验结果表明,相比单信道的图像盲复原算法,多信道的图像盲复原算法可以得到更好的复原结果。同时,与某些经典的多信道图像盲复原算法相比,提出的算法在复原效果方面具有一定的优势。

关键词: 图像复原,贝叶斯框架,先验模型,调和模型,信道互质

Abstract: In order to well utilize the information in the observed images and the complementarities between the information to improve the results of the image restoration, this paper proposed a blind restoration algorithm for multichannel images. Firstly, the prior models of the original image, point spread functions and the observed images were reconstructed, from which the prior distributions of them were obtained; secondly, the Uamma distribution was used to describe the unknown model parameters; finally, based on the inference of the max posterior probability, the optimal original image and the point spread functions were estimated using the evidence analysis method. Compared with the single channel algorithms, the experiments show that the multichannel blind image restoration can obtain better results. Meanwhile,the proposed algorithm shows competitive performance on restored results compared with some state-of-the-art algorithms.

Key words: Image restoration,Bayesian framework, Prior models, Harmonic model, Channel co-primeness

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