Image based rendering technique via sparse representation in shearlet domain
In this paper we propose a method for reconstructing a densely sampled light field from a given sparse set of perspective views from rectified cameras without an explicit estimation of the scene depth. The desired intermediate views are synthesized by inpainting of epipolar-plane images, utilizing their sparsity in the shearlet domain. For the purpose of shearlet-domain representation, compactly supported shearlets have been constructed using different directional filters for different scales in an attempt to provide better directional selectivity at lower scales. The reconstruction procedure with shearlet-domain sparsity condition is implemented through an iterative thresholding algorithm. The performance of the method is quantified by tests on synthetic and real visual data and compared favorably against depth-image based rendering.