Iterative adaptive hybrid image restoration for fast convergence

Citations

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SCOPUS

2

초록

We present an iterative adaptive hybrid image restoration algorithm for fast convergence. The local variance, mean, and maximum values are used to constrain the solution space. These parameters are computed at each iteration step using a partially restored image at each iteration, and they are used to impose the degree of local smoothness on the solution. The resulting iterative algorithm exhibits increased convergence speed and better performance than typical regularized constrained least-squares approach. (C) 2010 Society of Photo-Optical Instrumentation Engineers. [DOI: 10.1117/1.3479935]

키워드

restoration; iteration; local smoothness; convergence; regularized constrained least squares
제목
Iterative adaptive hybrid image restoration for fast convergence
저자
Hong, Min-Cheol
DOI
10.1117/1.3479935
발행일
2010-08
유형
Article
저널명
Optical Engineering
권
49
호
8