PSNR BASED OPTIMIZATION APPLIED TO ALGEBRAIC RECONSTRUCTION TECHNIQUE FOR IMAGE RECONSTRUCTION ON A MULTI-CORE SYSTEM
Abstract: The present work
attempts to reveal a parallel Algebraic Reconstruction Technique (pART) to
reduce the computational speed of reconstructing artifact-free images from
projections. ART is an iterative algorithm well known to reconstruct
artifact-free images with limited number of projections. In this work, a novel
idea has been focused on to optimize the number of iterations mandatory based
on Peak to Signal Noise Ratio (PSNR) to reconstruct an image. However, it suffers
of worst computation speed. Hence, an attempt is made to reduce the computation
time by running iterative algorithm on a multi-core parallel environment. The
execution times are computed for both serial and parallel implementations of
ART using different projection data, and, tabulated for comparison. The
experimental results demonstrate that the parallel computing environment
provides a source of high computational power leading to obtain reconstructed
image instantaneously.
Keywords: Image Processing,
Image Reconstruction, Iterative Image Reconstruction, Algebraic Reconstruction
Technique, Parallel Processing, OpenMP
Author: Bharathi Lakshmi
Agnimarimuthu, Christopher Durairaj Daniel Durairaj
Journal Code: jptkomputergg170011
