ICIP 2006, Atlanta, GA
 

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Paper:TP-L4.7
Session:Super-Resolution
Time:Tuesday, October 10, 16:40 - 17:00
Presentation: Lecture
Title: EFFICIENT SUPER-RESOLUTION RECONSTRUCTION FOR TRANSLATIONAL MOTION USING A NEAR LEAST SQUARES RESAMPLING METHOD
Authors: Harish Essaky Sankaran; Tampere University of Technology 
 Atanas Gotchev; Tampere University of Technology 
 Karen Egiazarian; Tampere University of Technology 
Abstract: In this paper we propose a computationally efficient method for image super-resolution reconstruction. We concentrate on pure translational motion and shift-invariant blur. This is the case of interlaced sampling where each low resolution image is uniformly sampled but the overall sampling is non-uniform with respect to the high resolution grid. The reconstruction problem is considered in a multi-resolution framework using separable B-spline wavelets as basis. This allows performing the reconstruction on a uniform higher resolution grid by digital filtering. A computationally efficient structure – the transposed modified Farrow structure is used to achieve a near least squares solution without using any matrix inversions or iterations. The reconstruction can also be performed at non-dyadic scales. Our method minimizes the aliasing distortions and gives results comparable with other least squares techniques.