首页    期刊浏览 2024年11月25日 星期一
登录注册

文章基本信息

  • 标题:A Bayesian Super-Resolution Approach to Demosaicing of Blurred Images
  • 本地全文:下载
  • 作者:Miguel Vega ; Rafael Molina ; Aggelos K. Katsaggelos
  • 期刊名称:EURASIP Journal on Advances in Signal Processing
  • 印刷版ISSN:1687-6172
  • 电子版ISSN:1687-6180
  • 出版年度:2006
  • 卷号:2006
  • DOI:10.1155/ASP/2006/25072
  • 出版社:Hindawi Publishing Corporation
  • 摘要:

    Most of the available digital color cameras use a single image sensor with a color filter array (CFA) in acquiring an image. In order to produce a visible color image, a demosaicing process must be applied, which produces undesirable artifacts. An additional problem appears when the observed color image is also blurred. This paper addresses the problem of deconvolving color images observed with a single coupled charged device (CCD) from the super-resolution point of view. Utilizing the Bayesian paradigm, an estimate of the reconstructed image and the model parameters is generated. The proposed method is tested on real images.

国家哲学社会科学文献中心版权所有