.png){kind=icon}
返回
Blind image deconvolution using a robust GCD approach
.png){kind=icon}
PRE
AI
DOI：10.1109/83.743863.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this correspondence, a new viewpoint is proposed for estimating an image from its distorted versions in presence of noise without the a priori knowledge of the distortion functions. In z-domain, the desired image can be regarded as the greatest common polynomial divisor among the distorted versions. With the assumption that the distortion filters are finite impulse response (FIR) and relatively coprime, in the absence of noise, this becomes a problem of taking the greatest common divisor (GCD) of two or more two-dimensional (2-D) polynomials. Exact GCD is not desirable because even extremely small variations due to quantization error or additive noise can destroy the integrity of the polynomial system and lead to a trivial solution. Our approach to this blind deconvolution approximation problem introduces a new robust interpolative 2-D GCD method based on a one-dimensional (1-D) Sylvester-type GCD algorithm. Experimental results with both synthetically blurred images and real motion-blurred pictures show that it is computationally efficient and moderately noise robust.
Keyword:
blind image deconvolution
equalization
image processing
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
13.7
论文数:
1.0W
被引数:
8.4W
机构
暂无机构信息
引用论文
分享收藏A data-driven approach for discovering stochastic dynamical systems with non-Gaussian Lévy noise
OAAI
OAAI分享收藏Synthesis of oxaspirolactones by manganic acetate promoted additions to exocyclic enol lactones.png)
Tetrahedron
TetrahedronIF0
PREAI
分享收藏分享收藏An approach to adhesive bond characterisation using guided acoustic waves in multi-layered plates
PREAI
分享收藏分享收藏
查看更多内容