|
It is believed by many that three-dimensional (3D) television will be the next logical development toward a
more natural and vivid home entertaiment experience. While classical 3D approach requires the transmission
of two video streams, one for each view, 3D TV systems based on depth image rendering (DIBR) require a
single stream of monoscopic images and a second stream of associated images usually termed depth images
or depth maps, that contain per-pixel depth information. Depth map is a two-dimensional function that
contains information about distance from camera to a certain point of the object as a function of the image
coordinates. By using this depth information and the original image it is possible to reconstruct a virtual
image of a nearby viewpoint by projecting the pixels of available image to their locations in 3D space
and finding their position in the desired view plane. One of the most significant advantages of the DIBR
is that depth maps can be coded more efficiently than two streams corresponding to left and right view
of the scene, thereby reducing the bandwidth required for transmission, which makes it possible to reuse
existing transmission channels for the transmission of 3D TV. This technique can also be applied for other
3D technologies such as multimedia systems.
In this paper we propose an advanced wavelet domain scheme for the reconstruction of stereoscopic
images, which solves some of the shortcommings of the existing methods discussed above. We perform the
wavelet transform of both the luminance and depth images in order to obtain significant geometric features,
which enable more sensible reconstruction of the virtual view. Motion estimation employed in our approach
uses Markov random field smoothness prior for regularization of the estimated motion field.
The evaluation of the proposed reconstruction method is done on two video sequences which are typically
used for comparison of stereo reconstruction algorithms. The results demonstrate advantages of the proposed
approach with respect to the state-of-the-art methods, in terms of both objective and subjective performance
measures.
|
