Title :
Super-resolution reconstruction of an image
Author :
Elad, M. ; Feuer, A.
Author_Institution :
Dept. of Electr. Eng., Technion-Israel Inst. of Technol., Haifa, Israel
Abstract :
This paper presents a generalization of restoration theory for the problem of super-resolution reconstruction (SRR) of an image. In the SRR problem, a set of low quality images is given, and a single improved quality image which fuses their information is required. We present a model for this problem, and show how the classic restoration theory tools-maximum likelihood estimator (ML), maximum a posteriori probability estimator (MAP) and the projection onto convex sets (POCS)-can be applied as a solution. A hybrid algorithm which joins the POCS and the ML benefits is suggested
Keywords :
image resolution; image restoration; iterative methods; maximum likelihood estimation; MAP; ML; POCS; hybrid algorithm; image quality; image restoration theory tools; iterative two phase algorithm; low quality images; maximum a posteriori probability estimator; maximum likelihood estimator; projection onto convex sets; restoration theory; stochastic perception; superresolution image reconstruction; Additive noise; Equations; Fuses; Image reconstruction; Image resolution; Image restoration; Maximum likelihood estimation; Noise measurement; Pollution measurement; Size measurement;
Conference_Titel :
Electrical and Electronics Engineers in Israel, 1996., Nineteenth Convention of
Conference_Location :
Jerusalem
Print_ISBN :
0-7803-3330-6
DOI :
10.1109/EEIS.1996.566997
