Abstract

Light field imaging involves reconstructing a 4D light field from a 3D focal stack, which makes it challenging to reconstruct the light field from incomplete projection data. To address this problem, a linear projection system is established to model the focal stack imaging process using discrete refocusing equations. Based on this system, we propose the block Landweber iterative method to find the least-squares solution. This method computes the sparse matrix while iterating, which overcomes the problem of data storage. The 2-norm of the block matrix is utilized as the weighted matrix to normalize every block matrix on an identical scale, delivering an effective relaxation strategy under the convergence condition in the inconsistent case, which yields better reconstruction results and accelerates the convergence speed. The experimental results based on the image quality assessments of reference and non-reference images show that our method achieved better reconstruction results compared to other relevant common methods, even with fewer focal stacks and higher angle resolution.

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