This paper deals with the technique for generating free viewpoint images by using multi-focus imaging sequences.
The method may enable us to realize dense 4-D ray-space reconstruction from 3-D multi-focus imaging sequences.
Previously, we proposed a method of generating free viewpoint, iris and focus images directly from multi-focus
imaging sequences with a 3-D convolution filter that expresses how the scene is defocused in the sequence.
However, the cost of the spatial frequency analysis based on 3-D FFT is not inexpensive. In this paper, efficient
reconstruction of free viewpoint images by dimension reduction and 2-D FFT is discussed. We show some
experimental results by using synthetic and real images. Epipolar plane images are also reconstructed in order
to show the disparity between generated free viewpoint images clearly.
This paper deals with a view interpolation problem using multiple images captured with a circular camera array.
An inverse filtering method for reconstructing a virtual image at the center of the camera array is proposed.
First, we generate a candidate image by adding all correspondence pixel values based on multiple layers assumed in a scene.
Second, we model a linear relationship between the desired virtual image and the candidate image, and then derive the inverse filter to reconstruct the virtual image.
Since we can derive the inverse filter independent of the scene structure,
the proposed method requires no depth estimation.
Simulation results using synthetic images show
that increasing the number of cameras and layers improves the quality of the virtual image.
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