Preconditioned iterative methods for high-resolution image reconstruction with multisensors

Abstract

We study the problem of reconstructing a high-resolution image from multiple undersampled, shifted, degraded frames with subpixel displacement errors. The corresponding reconstruction operators H is a spatially variant operator. In this paper, instead of using the usual zero boundary condition, the Neumann boundary condition is imposed on the images. The resulting discretization matrix of H is a block-Toeplitz-Toeplitz-block-like matrix. We apply the preconditioned conjugate gradient (PCG) method with cosine transform preconditioner to solve the discrete problems. Preliminary results how that the image model under the Neumann boundary condition gives better reconstructed high-resolution images than that under the zero boundary condition, and the PCG method converges very fast.