Wavelet-based reconstruction of irregularly-sampled images: application to stereo imaging

We are concerned with the reconstruction of a regularly-sampled image based on irregularly-spaced samples thereof. We propose a new iterative method based on a wavelet representation of the image. For this representation we use a biorthogonal spline wavelet basis implemented on an oversampled grid. We apply the developed algorithm to disparity-compensated stereoscopic image interpolation. Under disparity compensation, the resulting sampling grids are irregular and require the irregular/regular interpolation. We show the experimental results on real-world images and we compare our results with other methods proposed in the literature.