Four Projections CMOS Linear Image Sensor Tomographic Image Reconstruction
DOI:
https://doi.org/10.11113/jt.v61.1631Keywords:
Optical tomography, linear back-projection, CMOS linear image sensorAbstract
This study focused on developing software for image reconstruction system of optical image data obtained from four projections of CMOS linear image sensors by using MATLAB. Four projections of collimated light beams at least must be used in order to avoid aliasing and smear effect that may be appeared on the reconstructed image obtained. The image reconstruction is based on linear back-projection method where transpose matrix, and pseudo-inverse matrix are used to solve inverse matrix problems in MATLAB. Results were compared between both inverse problem calculation methods selected. It was discovered that transpose matrix method performs better than pseudo–inverse matrix for a high resolution images. A graphical user interface has been implemented, it is capable to reconstruct image from raw data collected from sensor. Reconstruction results demonstrated in most cases are able to produce an adequate image for further analysis by user.References
A. Charette, J. Boulanger and H. K. Kim. 2008. An Overview on Recent Radiation Transport Algorithm Development for Optical Tomography Imaging. Journal of Quantitative Spectroscopy & Radiative Transfer. 109. 2743–2766.
R. Cierniak. 2009. New Neural Network Algorithm for Image Reconstruction from Fan-Beam Projections. Journal of Neuro-computing. 72. 3238–3244.
X. B. Dai, H. Z. Shu, L. M. Luo, G. N. Han and J. L. Coatrieux. 2010. Reconstruction of Tomographic Images from Limited Range Projections using Discrete Radon Trnasform and Tchebichef Moments. Journal of Pattern Recognition. 43. 1152-1164.
A. A. Desai. 2008. Computer Graphics. Earstern Economy Edition. New Delhi: PHI Learning Pvt. Ltd. 97–99.
F. Faille and M. Petrou. 2010. Invariant Image Reconstruction from Irregular Samples and Hexagonal Grid Splines. Journal of Image and Vision Computing. 28: 1173–1183.
T. H. Gabor.2001. A Note on Exact Image Reconstruction from a Limited Number of Projections. Journal of Visual Communication and Image Representation. 20. 65–67.
A. L. Kesidis and N. Papamarkos. 2008. Exact Image Reconstruction from a Limited Number of Projections. Journal of Visual Communication and Image Representation. 19. 285–298.
S. C Mukhopadhyay, A. Lay-Ekuakille, and A. Fuchs. 2011. New Developments and Applications in Sensing Technology. New York: Springer. 84–86.
F. Natterer,and F. Wübbeling. 2001. Mathematical Methods in Image Reconstruction USA: Cambridge University Press. 81–110.
R. Parekh. 2006. Principles of Multimedia. New Delhi: Tata McGraw-Hill Education. 128.
J. J. Park. 2012. Computer Science and Convergence: CSA 2011 & WCC 2011 Proceedings. New York : Springer. 842–844.
M. F. Rahmat and, H. Ahmed Sabit. 2005. Flow Regime Identification and Concentration Distribution of Solid Particles Flow in Pipelines using Electrodynamic Tomography and Artificial Neural Networks. Proceeding of the 9th International Conference on Mechatronics Technology, Kuala Lumpur.
T. Tarvainen, M. Vauhkonen and S. R. Arridge. 2008. Gauss-Newton Reconstruction Method for Optical Tomography Using the Finite Element Solution of the Radiative Transfer Equation. Journal of Quantitative Spectroscopy & Radiative Transfer. 109(2008): 2767–2778.
I. R. Terol, J. D. Mendiola and S. L. Canchola. 2006. Image Segmentation and Filtering based on Transformations with Reconstruction Criteria. Journal of Visual Communication and Image Representation. 17(2006): 107–130.
J. Tian and K. K. Ma. 2010. Stochastic Super-Resolution Image Reconstruction. Journal of Visual Communication and Image Representation. 21(2010): 232–244.
S. L. Wood. 2009. Super-Resolution Image Reconstruction for a Steerable Array of Sub-Imagers. Journal of Digital Signal Processing. 19(2009): 932–933.
D. Zhang, H. F. Li and M. H. Du. 2005. Fast MAP-based Multiframe Super Resolution Image Reconstruction. Journal of Image and Vision Computing. 23(2005): 671–679.
Downloads
Published
Issue
Section
License
Copyright of articles that appear in Jurnal Teknologi belongs exclusively to Penerbit Universiti Teknologi Malaysia (Penerbit UTM Press). This copyright covers the rights to reproduce the article, including reprints, electronic reproductions, or any other reproductions of similar nature.
