Wavelet-based iterative perfect reconstruction in computational integral imaging.

We propose a new computational integral imaging (CII) method via the iterative perfect reconstruction technique to improve the visual quality of reconstructed 3D scenes. As is well known, images reconstructed by CII suffer from artifacts and, as a result, degradation of visual quality. As solutions to this problem, the regularization and iterative back-projection (IBP)-based super-resolution (SR) reconstruction algorithms have been shown to be effective for high-visual-quality reconstruction. However, computation of the regularization algorithm is very expensive, and the IBP algorithm is very sensitive to noise in the deblurring process. To address these challenges, we propose an iterative perfect reconstruction algorithm that addresses the issues of low visual quality and noise sensitivity. Experimental results indicate that our proposed method outperforms the conventional SR reconstruction-based CII methods.