The TOMBO system (thin observation module by bound optics) is a multichannel subimaging system over a single electronic imaging device. Each subsystem provides a low-resolution (LR) image from a unique lateral point of view. By estimating the image's lateral position, a high-resolution (HR) image is restored from the series of the LR images. This paper proposes an multistage algorithm comprised of successive stages, improving difficulties in previous suggested schemes. First, the registration algorithm estimates the subchannel shift parameters and eliminates bias. Second, we introduce a fast image fusion, overcoming visual blockiness artifacts that characterized previously suggested schemes. The algorithm fuses the set of sampled subchannel images into a single image, providing the reconstruction initial estimate. Third, an edge-sensitive quadratic upper bound term to the total variation regulator is suggested. The complete algorithm allows the reconstruction of a clean, HR image, in linear computation time, by the use of the linear conjugate gradient optimization. Finally, we present a simulated comparison between the proposed method and a previously suggested image restoration method. The results show that the proposed method yields better reconstruction fidelity while eliminating spatial speckle artifacts associated with the previously suggested method.