Reconstruction of multiview images taken with non-regular sampling sensors

Increasing spatial image resolution is a widely discussed area in the field of image processing. In this paper, we present an efficient reconstruction approach for high-resolution images, taken with irregularly shielded low-resolution sensors in a multiview setup. The approach is based on the sparsi...

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Bibliographic Details
Main Authors: Richter, Thomas, Jonscher, Markus, Schnurrer, Wolfgang, Seiler, Jurgen, Kaup, Andre
Format: Conference Proceeding
Language:English
Subjects:
Cameras
depth-image based rendering
Gain
Image reconstruction
Image resolution
Image sensors
Multiview
non-regular sampling
PSNR
Sensors
sparsity
Online Access:Request full text
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Summary:Increasing spatial image resolution is a widely discussed area in the field of image processing. In this paper, we present an efficient reconstruction approach for high-resolution images, taken with irregularly shielded low-resolution sensors in a multiview setup. The approach is based on the sparsity assumption, meaning that natural images can be efficiently represented in a transform-domain using only few coefficients. Utilizing information from adjacent cameras results in a better reconstruction quality for the central high-resolution view. Since neighboring camera perspectives might differ in illumination, the information from adjacent views has to be adapted to the view to be reconstructed. The simulation results show that a proper incorporation of information from neighboring views leads to a PSNR gain of up to 2.20 dB compared to a state-of-the-art singleview reconstruction approach.
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.2014.6854713