A variational approach to recovering depth from defocused images

Author

Rajagopalan, A.N. ; Chaudhuri, S.

Author_Institution

Dept. of Electr. Eng., Indian Inst. of Technol., Bombay, India

Volume

19

Issue

10

fYear

1997

fDate

10/1/1997 12:00:00 AM

Firstpage

1158

Lastpage

1164

Abstract

In this paper, we propose a regularized solution to the depth from defocus (DFD) problem using the space-frequency representation (SFR) framework. A smoothness constraint is imposed on the estimates of the blur parameter, and a variational approach to the DFD problem is developed. Among the numerous SFRs, we study the applicability of the complex spectrogram and the Wigner distribution, in particular, for depth recovery. The performance of the proposed variational method is tested on both synthetic and real images. The method yields good results, and the quality of the estimates is significantly better than that obtained without the smoothness constraint on the blur parameter

Keywords

artificial intelligence; computer vision; image restoration; variational techniques; Wigner distribution; blur parameter estimates; complex spectrogram; depth from defocused images recovery; real images; regularized solution; smoothness constraint; space-frequency representation; synthetic images; variational approach; variational method; Amplitude estimation; Apertures; Cameras; Design for disassembly; Filtering; Focusing; Frequency estimation; Layout; Parameter estimation; Spectrogram;

fLanguage

English

Journal_Title

Pattern Analysis and Machine Intelligence, IEEE Transactions on

Publisher

ieee

ISSN

0162-8828

Type

jour

DOI

10.1109/34.625126

Filename

625126