Abstract
In this paper, the 3D integral imaging method is extended to situations
where the sensor positions in the image pick up stage are unknown.
Conventional integral imaging systems require a priori knowledge of sensor
positions in the image capture stage which can be difficult to measure in
synthetic aperture or randomly distributed sensors modes. In the proposed
method, only the relative position of two sensors is needed whereas all
other sensors positions are unknown. We combine image correspondences
extraction, camera perspective model, two view geometry and computational
integral imaging 3D reconstruction techniques to overcome this limitation in
integral imaging systems. The image reconstruction quality of the system
with unknown sensor positions is compared with conventional integral imaging
with known sensor positions. We also demonstrate how the proposed method may
be used to improve the image reconstruction quality even in situations where
the sensor positions recorded are subject to measurement
errors.
© 2010 IEEE
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