Self-similarity modeling for interpolation and extrapolation of multi-viewpoint image sets

For the 3-D image communication, a flexible interpolation technique of a multi-viewpoint image set (MVIS) is required. If we could recover the 3-D structure from an MVIS, interpolative images would be obtained. This approach, however, can not be easily applied to arbitrary objects because of the difficulty in stereo-matching. In this paper, the self-similarity modeling which has been studied in the field of data compression is chosen as a modeling scheme which is scalable to any resolution, and the interpolation is virtually achieved by enhancing the resolution of the viewpoint-axis of an MVIS. This new approach is free from stereo-matching and is shown to achieve interpolative images with an SNR of about 35 dB