3 citations · 3 across the 5 of their papers we have counts for
8 papers
Subpixel image reconstruction using nonuniform defocused images
Hieu Thao Nguyen, Oleg Soloviev, Jacques Noom +1
This paper considers the problem of reconstructing an object with high-resolution using several low-resolution images, which are degraded due to nonuniform defocus effects caused b…
Nonuniform Defocus Removal for Image Classification
Nguyen Hieu Thao, Oleg Soloviev, Jacques Noom +1
We propose and study the single-frame anisoplanatic deconvolution problem associated with image classification using machine learning algorithms, named the nonuniform defocus remov…
Blind multi-frame deconvolution for the correction of space-variant blur in images
Wouter van de Ketterij, Oleg Soloviev, Michel Verhaegen
This paper demonstrates a practical method that can correct spatial varying blur from a set of images of the same object. The algorithm jointly estimates the object and local point…
Shack-Hartmann sensor as an imaging system with a phase diversity
Oleg Soloviev, Hieu Thao Nguyen, Vitalii Bezzubik +3
Conventional methods of wavefront reconstruction from the raw data of the Shack-Hartmann sensor use the focal spot shifts and discard the high-frequency information about the wavef…
Convex combination of alternating projection and Douglas-Rachford operators for phase retrieval
Nguyen Hieu Thao, Oleg Soloviev, Michel Verhaegen
We present the convergence analysis of convex combination of the alternating projection and Douglas-Rachford operators for solving the phase retrieval problem. New convergence crit…
Blind single-frame deconvolution by tangential iterative projections (TIP)
Dean Wilding, Oleg Soloviev, Paolo Pozzi +3
Deconvolution serves as a computational means of removing the effect of optical aberrations from recorded images and is employed in many technical and scientific fields of study. I…