New Image Registration Techniques: Development and Comparative Analysis

Sindhu Madhuri G., Indra Gandhi M. P.

Abstract


Design and Development of new Image Registration Techniques by using complex mathematical transformation functions are attempted in this research work as there is a requirement for the performance measurement of image registration complexity. The design and development of new image registration techniques are carried out with complex mathematical transformations of Radon and Slant functions due to their importance. And the rotation and translation geometric function are considered for better insight into the complex image registration process. The newly developed image registration techniques areevaluated and analyzed with openly available images of Lena, Cameraman and VegCrop. The accuracy as a performance measure of the newly developed image registration techniques are attempted to measure with popularly known metrics of RMSE, PSNR and Entropy. And the results obtained after successful image registration process are compared are presented. It is observed from the results that the developed new image registration techniques using Radon and Slant transformation functions with rotation and translation are superior and useful for the requirement and purpose in the digital image processing domain. Finally a research effort is made to development of new image registration techniques that are useful to extract intelligence embedded in the images with complex transformation function and an attempt is made to measure its performance also.

Full Text:

PDF

References


Annadurai, S. and Lakshmi R.S. Fundamentals of Digital Image Processing, Pearson, 2007. [2] Barbara Z. And Flusser J., “Image registration methods: a survey”, Image and Vision Computing, Vol. 21, pp. 977-1000, 2003. [3] Brown, L.G., “A Survey of Image Registration Techniques, ACM Computer Surveys”, ACM Computer Surveys, Vol. 24, No. 4, pp. 325-376, 1992. [4] Gonzalez, R.C. and Woods, R.E., Digital Image Processing, 2nd Ed. Pearson, 2002. [5] Goshtasby, A.A., 2-D and 3-D Image Registration for Medical, Remote Sensing, and Industrial Applications, Wiley Press, 2005. [6] Goshtasby, A.A., Image Registration: Principles, Tools and Methods,Springer, 2012. [7] Jayaraman, S., Esakkirajan, S., and Veerakumar, R., Digital Image Processing, Tata McGraw Hill, 2011. [8] Jignesh, N.S. and Patnaik, S., “Automatic Image Registration Using Mexican Hat Wavelet, Invariant Moment and Radon Transform”, International Journal of Advanced Computer Science and Applications, Special Issue on Image Processing and Analysis, pp 75-84, 2011. [9] Kekre, H. B., Tanuja, K.S. and Ruhina, B.K., “2 D Satellite Image Registration using transform based and correlation based methods”, International Journal of Advanced Computer Science and Applications, Vol. 3, No. 5, pp 66-72, 2011. [10] Pratt, W.K., “Slant Transform Image Coding”, IEEE Transactions on Communications, 1974. [11] Madhuri, G.S., “Classification of Image Registration Techniques and Algorithms in Digital ImageProcessing - A Research Survey”, International Journal of Computational Trends and Technology, Vol. 15, No. 2, pp. 78-82, 2014.

Madhuri, G.S. and Indra, M.P.G. (2015),“Image Registration Quality Assessment with Similarity Measures -AResearch Study”, IEEE eXplore, ISBN 978-1-4799-8080-2.

Madhuri, G.S. and Indra, M.P.G., “Image Registration with Similarity Measures using CorrelationTechniques - A Research Study”, IEEE eXplore, ISBN 978-1-4799-7848-9, 2015.

Madhuri,G.S. and Indra, M.P.G., “New Methodology for Image Registration - An Application to Digital Image Processing”, International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 6, No. 7, pp. 364-368, 2016.

Meyer, A.B. and Schmid V. J., Pattern Recognition and Signal Analysis in Medical Imaging, Academic Press, 2014.

Pratt, W.K., “Correlation Techniques of Image Registration”, IEEE Transactions on Aerospace and Electronic Systems, Vol. 10, No. 3, 1974.

Robinson, D. and Milanfar, P., “Fundamental performance limits in image registration”, IEEE transactions on image processing, Vol. 13, No. 9, pp. 1185-1199, 2004.

Selesnick, I.W., “The Slantlet Transform”, IEEE Trans on Signal Processing, vol. 47, No. 5., 1999.

Shajan, P.X., Muniraj, N.J.R. and John, T.A., “3D/4D Image Registration and Fusion Techniques: A Survey”, International Journal of Computer Science and Information Technologies, Vol. 3, No. 4, pp 4829-4839, 2012.

Shehan F. and, Cooray, T., Rotation Invariant Image Registration with Radon Transform, SAITM Research Symposium on Engineering Advancement, pp 51-54, 2011.

Szeliski, R., Computer Vision: Algorithms and Applications, Springer, 2010.

Wohlberg, G. and Zokai, G., “Robust Image Registration Using Log Polar Transform, IEEE International Conference on Image Processing, NASA (NAG-57129), 2000.

Zahra Hosein Nejad and Mehdi Nasri, RKEM: Redundant Keypoint Elimination Method in Image Registration, vol. 11, Issue 5, pp. 273-284, The IET Image Processing,, 2017.

Zhu, Y. M., “Volume Image Registration by Cross Entropy Optimization”, IEEE Transactions on Medical Imaging, Vol. 21, No. 2, pp 174-180, 2002.




DOI: https://doi.org/10.23956/ijermt.v6i7.204

Refbacks

  • There are currently no refbacks.