<abstract xmlns="http://www.w3.org/1999/xhtml"><p> The travel time tomography technology had achieved wide application, the hinge of tomography was inversion algorithm, the ray path tracing technology had a great impact on the inversion results. In order to improve the SNR of inversion image, comprehensive utilization of inversion results with different ray tracing can be used. We presented an imaging fusion method based on improved Wilkinson iteration method. Firstly, the shortest path method and the linear travel time interpolation were used for forward calculation; then combined the improved Wilkinson iteration method with super relaxation precondition method to reduce the condition number of matrix and accelerate iterative speed, the precise integration method was used to solve the inverse matrix more precisely in tomography inversion process; finally, use wavelet transform for image fusion, obtain the final image. Therefore, the ill-conditioned linear equations were changed into iterative normal system through two times of treatment and using images with different forward algorithms for image fusion, it reduced the influence effect of measurement error on imaging. Simulation results showed that, this method can eliminate the artifacts in images effectively, it had extensive practical significance.</p></abstract>

The travel time tomography technology had achieved wide application, the hinge of tomography was inversion algorithm, the ray path tracing technology had a great impact on the inversion results. In order to improve the SNR of inversion image, comprehensive utilization of inversion results with different ray tracing can be used. We presented an imaging fusion method based on improved Wilkinson iteration method. Firstly, the shortest path method and the linear travel time interpolation were used for forward calculation; then combined the improved Wilkinson iteration method with super relaxation precondition method to reduce the condition number of matrix and accelerate iterative speed, the precise integration method was used to solve the inverse matrix more precisely in tomography inversion process; finally, use wavelet transform for image fusion, obtain the final image. Therefore, the ill-conditioned linear equations were changed into iterative normal system through two times of treatment and using images with different forward algorithms for image fusion, it reduced the influence effect of measurement error on imaging. Simulation results showed that, this method can eliminate the artifacts in images effectively, it had extensive practical significance.

Image Fusion for Travel Time Tomography Inversion

College of Computer and Information, Hohai University, Nanjing 210098, China

The Fourth Department, Bengbu Naval Petty Officer Academy, Bengbu 233012, China

College of Information Engineering, Anhui Science and Technology University, Chuzhou 233100, China

Department of Geology, Faculty of Science, University Of Malaya 50603 Kuala Lumpur, Malaysia

Faculty of Science & Natural Resources, Universiti Malaysia Sabah, 88400 Kota Kinabalu, Sabah, Malaysia

Polish Maritime Research

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"Image Fusion for Travel Time Tomography Inversion"}

The travel time tomography technology had achieved wide application, the hinge of tomography was inversion algorithm, the ray path tracing technology had a...

Image Fusion for Travel Time Tomography Inversion

Published Online: Oct 15, 2015

Page range: 149 - 156

DOI: https://doi.org/10.1515/pomr-2015-0047

Keywords
tomography, inversion algorithm, wavelet transform, image fusion

© 2015

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Image Fusion for Travel Time Tomography Inversion

Published Online: Oct 15, 2015

Page range: 149 - 156

DOI: https://doi.org/10.1515/pomr-2015-0047

Keywordstomography, inversion algorithm, wavelet transform, image fusion

© 2015

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Keywords
tomography, inversion algorithm, wavelet transform, image fusion