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Exact image reconstruction from a limited number of projections
Affiliation:1. State Key Laboratory of Virtual Reality Technology and Systems, School of Computer Science, Beihang University, China;2. Stony Brook University (SUNY Stony Brook), USA;1. LATIS ENISo, National Engineering School of Sousse, University of Sousse, Tunisia;2. Institut Pascal, Clermont Auvergne University, France;1. Xi’an Jiaotong-Liverpool University, Suzhou, China;2. Beijing Jiaotong University, Beijing, China;1. Italian Institute of Technology, RBCS (Robotics, Brain, and Cognitive Sciences) Department, Genoa, Italy;2. University of Essex, School of Computer Science and Electronic Engineering, Wivenhoe Park, CO34SQ, UK
Abstract:A new method for the exact reconstruction of any gray-scale image from its projections is proposed. The original image is projected into several view angles and the projection samples are stored in an accumulator array. In order to reconstruct the image, the accumulator array is considered as an accumulation of sinusoidal contributions each one corresponding to a certain pixel of the original image. The proposed method defines conditions for the necessary number of projections and the density of ray samples on the projection axis. These conditions insure that, for each pixel, there is at least one sample in the accumulator array where only this particular pixel contributes. This characteristic projection sample is used during the reconstruction phase to determine the coordinates and the gray-scale value of the corresponding image pixel. A variation of the method is also proposed where the reconstruction is performed using a limited number of projection samples in certain view angles. Specifically, the number of necessary samples equals at most the overall number of pixels in the original image. This approach leads to a significant reduction of memory and processing time requirements since it provides exact image reconstruction using one projection sample per pixel.
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