DocumentCode :
249414
Title :
Adaptive scale selection for multiresolution defocus blur estimation
Author :
Karaali, Ali ; Rosito Jung, Claudio
Author_Institution :
Inst. of Inf., Fed. Univ. of Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
fYear :
2014
fDate :
27-30 Oct. 2014
Firstpage :
4597
Lastpage :
4601
Abstract :
This paper presents a new method for defocus blur estimation using a single image. The proposed method exploits the ratio of gradient magnitude images computed at multiple scales, using the scale-space theory to estimate the number of reliable scales. Experimental results on synthetic and real images show that the proposed method is robust to noise, edge mis-localization and neighboring edge interference. We also show a new application of blur estimation algorithms to perform image re-targeting algorithms, leading to in-focus object preservation.
Keywords :
edge detection; adaptive scale selection; edge mislocalization; gradient magnitude images; image re-targeting algorithm; in-focus object preservation; multiresolution defocus blur estimation algorithm; neighboring edge interference; real images; scale-space theory; synthetic images; Estimation; Image edge detection; Interference; Kernel; Robustness; White noise; defocus blur estimation; multiscale analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2014 IEEE International Conference on
Conference_Location :
Paris
Type :
conf
DOI :
10.1109/ICIP.2014.7025932
Filename :
7025932
Link To Document :
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