The imaging properties of small cameras in mobile devices exclude restricted depth-of-field and range-dependent blur that may provide a sensation of depth. Algorithmic solutions to this problem usually fail because high- quality, dense range maps are hard to obtain, especially with a mobile device. However, methods like stereo, shape from focus stacks, and the use of ashlights may yield coarse and sparse range maps. A standard procedure is to regularize such range maps to make them dense and more accurate. In most cases, regularization leads to insufficient localization, and sharp edges in depth cannot be handled well. In a wavelet basis, an image is defined by its significant wavelet coefficients, only these need to be encoded. If we wish to perform range-dependent image processing, we only need to know the range for the significant wavelet coefficients. We therefore propose a method that determines a sparse range map only for significant wavelet coefficients, then weights the wavelet coefficients depending on the associate range information. The image reconstructed from the resulting wavelet representation exhibits space-variant, range-dependent blur. We present results based on images and range maps obtained with a consumer stereo camera and a stereo mobile phone.

Date Published: 7 March 2013
PDF: 8 pages
Proc. SPIE 8667, Multimedia Content and Mobile Devices, 86671U (7 March 2013); doi: 10.1117/12.2002330

Published in SPIE Proceedings Vol. 8667:
Multimedia Content and Mobile Devices
Reiner Creutzburg; Todor G. Georgiev; Dietmar Wüller; Cees G. M. Snoek; Kevin J. Matherson; David Akopian; Andrew Lumsdaine; Lyndon S. Kennedy, Editor(s)