Which side of the focal plane are you on?


Autoria(s): Sellent, Anita; Favaro, Paolo
Data(s)

2014

Resumo

Defocus blur is an indicator for the depth structure of a scene. However, given a single input image from a conventional camera one cannot distinguish between blurred objects lying in front or behind the focal plane, as they may be subject to exactly the same amount of blur. In this paper we address this limitation by exploiting coded apertures. Previous work in this area focuses on setups where the scene is placed either entirely in front or entirely behind the focal plane. We demonstrate that asymmetric apertures result in unique blurs for all distances from the camera. To exploit asymmetric apertures we propose an algorithm that can unambiguously estimate scene depth and texture from a single input image. One of the main advantages of our method is that, within the same depth range, we can work with less blurred data than in other methods. The technique is tested on both synthetic and real images.

Formato

application/pdf

Identificador

http://boris.unibe.ch/67331/1/sellent2014which.pdf

Sellent, Anita; Favaro, Paolo (2014). Which side of the focal plane are you on? In: 2014 IEEE International Conference on Computational Photography (ICCP) (pp. 1-8). IEEE 10.1109/ICCPHOT.2014.6831818 <http://dx.doi.org/10.1109/ICCPHOT.2014.6831818>

doi:10.7892/boris.67331

info:doi:10.1109/ICCPHOT.2014.6831818

Idioma(s)

eng

Publicador

IEEE

Relação

http://boris.unibe.ch/67331/

http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=6831818

Direitos

info:eu-repo/semantics/restrictedAccess

Fonte

Sellent, Anita; Favaro, Paolo (2014). Which side of the focal plane are you on? In: 2014 IEEE International Conference on Computational Photography (ICCP) (pp. 1-8). IEEE 10.1109/ICCPHOT.2014.6831818 <http://dx.doi.org/10.1109/ICCPHOT.2014.6831818>

Palavras-Chave #000 Computer science, knowledge & systems #510 Mathematics
Tipo

info:eu-repo/semantics/conferenceObject

info:eu-repo/semantics/publishedVersion

PeerReviewed