An Efficient Satellite Image Super Resolution Technique for Shift-Variant Images using Improved New Edge Directed Interpolation

  • Pooja Solanki Post Graduate Student
  • Dippal Israni Assistant Professor
  • Arpita Shah Assistant Professor
Keywords: Dual Tree Complex Wavelet Transform (DT-CWT), Sub pixel shift, Resolution enhancement (RE), improved NEDI

Abstract

Super resolution is a method that reconstructs a higher resolution image from single captured image or set of captured low resolution images. Super resolution imaging is used for several image processing applications like medical imaging, earth observation systems and surveillance systems. Image interpolation is one of the conventional methods used to enhance the resolution of the image. Basic linear interpolation methods like bilinear, bicubic give the blurred image as a result. Non-linear interpolation methods like New Edge Directed Interpolation (NEDI), Curvature based interpolation, neural network based interpolation enhance the image but has limitations like several artifacts. In this paper, a novel innovative approach is proposed in which using dual tree complex wavelet transform (DT-CWT), low and high frequency sub bands are generated. High frequency sub band images are interpolated using improved NEDI which is NEDI with a circular window and dynamic window. Improved NEDI (INEDI) algorithm proposed in the paper gives better results on high frequency components which lead to high resolution image without artifacts. Inverse DT-CWT is applied on interpolated sub bands to reconstruct high resolution image. Registration is applied on both images and shift adaptable bilinear interpolation is applied which reconstructs image into 4 interpolation factor. The proposed approach is verified for different interpolation factors and for different satellite images. The accuracy of proposed approach is verified by several contrast features. The algorithm proposed in this paper outperforms in comparison to state of the art algorithms.

Author Biographies

Pooja Solanki, Post Graduate Student
Pooja Solanki is a Post Graduate student at U and P U patel, Department of Computer Engineering at Chandubhai S. Patel Institute of Technology, CHARUSAT, Gujarat.  Her research interests are Computer Vision, Image Processing andMachine Learning.
Dippal Israni, Assistant Professor
Dippal Israni is currently working as anAssistant Professor at Chandubhai S. PatelInstitute of Technology, CHARUSAT, Gujarat.He received his Bachelor of Engineering degreein Information Technology from Sardar PatelUniversity, Gujarat (India), and Master ofTechnology degree in Computer Engineeringfrom Dharmsinh Desai University, Gujarat(India). His research interests are ComputerVision, Image Processing and MachineLearning.
Arpita Shah, Assistant Professor
Arpita Shah is currently working as an AssistantProfessor at Chandubhai S. Patel Institute ofTechnology, CHARUSAT, Gujarat. Herresearch interests are Cloud Computing,Computer Vision, Image Processing andMachine Learning.

References

Z.Wang, Q. Zhang, X. Han, Satellite Remote Sensing Image Super Resolution Based On Markov Random Fields, International Geoscience and Remote Sensing Symposium, vol. 2, no. 1, pp. 183–202, 2009.

S. Vishnukumar, M. Wilscy, Super-resolution for Remote Sensing Images using Content Adaptive Detail Enhanced Self Examples, The International Conference on Circuit, Power and Computing Technologies (ICCPCT), Nagercoil, India, pp. 1-5, 2016.

W. Xinlei, L. Naifeng, Super-resolution of remote sensing images via sparse structural manifold embedding, Neuro computing, vol.173, no. 3, pp. 1402-1411, 2016.

M. Luz and M. Moklyachuk,Minimax interpolation problem for random processes with stationary increments,Statistics,Optimization & Information Computing, vol. 3, no.1, pp.30-41, 2015.

Z. Shen, Z. Geng and J. Yang Image reconstruction from incomplete convolution data via total variation regularization, Statistics,Optimization & Information Computing, vol. 3, no. 1, pp.1-14, 2015.

D. Wallach, Super-resolution in 4D positron emission tomography, Proceedings of IEEE Nuclear Science Symposium Conference,pp. 4285 4287,2008.

Z.Wang, Q. Zhang, X. Han, Super-resolved spatially encoded single-scan 2D MRI, An Official Journal of the International Society for Magnetic Resonance in Medicine, vol. 63, no. 6, pp. 1594-1600, 2010.

A. Gholipour, J. A. Estroff, S. K. Warfield, Robust super-resolution volume reconstruction from slice acquisitions: Application to fetal brain MRI, IEEE Transactions on Medical Imaging, vol. 29, no. 10, pp. 1739 1758, 2010.

P. Akhtar, F. Azhar, A single image interpolation scheme for enhanced super resolution in bio-medical imaging, Proceedings of 4th International Conference on Bioinformatics and Biomedical Engineering, pp. 1-5, 2010.

L. Kang, Y. Chen, Z. Yu, H. Wu, Z. Zheng and S. Niu, A Splitting based Iterative Method for Sparse Reconstruction, Statistics,Optimization & Information Computing, vol. 4, no. 1, pp.57-67, 2016.

L. Zhang, H. Zhang, H. Shen, P. li, A super-resolution reconstruction algorithm for surveillance images, Signal Processing vol. 90,no. 3, pp. 848-859, 2010.

X. Yan, Q. Shen, X. Liu, Super-resolution Reconstruction for License Plate Image in Video Surveillance System, 10th International Conference on Communications and Networking in China (ChinaCom) , pp. 643-657, 2015.

T. Uiboupin, P. Rasti, G. Anbarjafari, H. Demirel, Facial image super resolution using sparse representation for improving face recognition in surveillance monitoring, Proceedings of 24th IEEE Signal Processing and Communication Application Conference,Zonguldak, Turkey, pp. 437-440, 2016.

V. Choulakian, Matrix Factorizations Based on Induced Norms, Statistics, Optimization & Information Computing, vol. 4, no. 1,pp. 1-14, 2016.

M. G. Kang, S. Chauduri, Super-resolution image reconstruction,IEEE Signal Processing Magazine, vol. 20, pp. 3, pp. 19-20, 2003.

R.Y. Tsai, T.S. Huang, Multiframe image restoration and registration, Advances in Computer Vision and Image Processing, JAI Press Inc., Greenwich, London 1984.

D. Israni, H. Mewada, Feature Descriptor Based Identity Retention and Tracking of Players Under Intense Occlusion in Soccer Videos, International Journal of Intelligent Engineering and Systems, vol. 11, no. 4, pp:31-41, 2018.

N. Nguyen, P. Milanfar, A wavelet-based interpolation-restoration method for super resolution, Circuits, Systems and Signal Processing Magazine, Springer vol. 19, no. 4, pp. 321-338, 2000.

S. Rhee, M.G. Kang, Discrete cosine transform based regularized high-resolution image reconstruction algorithms, Optical Engineering, vol. 38, no. 8, pp. 1348-1356, 1999.

H. Ji, C. Fermuller, Wavelet-based super-resolution reconstruction: theory and algorithm, Proc. of the 9th European conference on Computer Vision Springer, Berlin, Heidelberg, pp. 295-307, 2006.

H. Ji, C. Fermuller, Robust wavelet-based super-resolution reconstruction: theory and algorithm, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 31, no. 4, pp. 649-660, 2009.

S. E. El-Khamy, M. M. Hadhoud, M. I. Dessouky, Bassiouny M.Salam, Regularized super-resolution reconstruction of images using wavelet fusion, Optical Engineering, vol. 44, no. 9, 2005.

S. E. El-Khamy, M. M. Hadhoud, M. I. Dessouky, Bassiouny M.Salam, Wavelet fusion: a tool to break the limits on LMMSE image super-resolution, International Journal of Wavelets, Multiresolution and Information Processing, vol. 4, no. 1, pp. 105-118, 2006.

M. B. Chappalli, N. K. Bose, Simultaneous noise filtering and super resolution with second-generation wavelets, IEEE Signal Processing Letters, vol. 12, no. 11, pp. 772-775, 2005.

H. Ur, D. Gross, Improved resolution from subpixel shifted pictures, CVGIP: Graphical Models and Image Processing, vol 54, no.2, pp. 181-186, 1992.

N. K. Bose, N.A. Ahuja, Super resolution and noise filtering using moving least squares, IEEE Transactions on Image Processing,vol. 15, no.8, pp. 2239 - 2248, 2006.

A. J. Patti, A. M. Tekalp, Super resolution video reconstruction with arbitrary sampling lattices and nonzero aperture time, IEEE Transactions on Image Processing, vol. 6, no. 8, pp. 1064 C 1076, 1997.

Q. Zhang, J. Wu, Image super-resolution using windowed ordinary Kriging interpolation, Optics Communications, vol. 336, pp.140-145, 2015.

J. Shi, Z. San, Directional variation adaptive image resolution enhancement, Optics Communications, vol. 285, no. 7, pp. 1692-1696, 2012.

M. Irani, S, Peleg, Improving resolution by image registration,CVGIP: Graphical Models and Image Processing, vol. 53, no. 3, pp.231-239, 1991.

S. Zhang, Satellite Remote Sensing Image Super Resolution Based On Markov Random Fields, Digital hologram resolution enhancement using a fast reconstruction algorithm, Optics Communications, vol. 332, pp. 158-163, 2014.

B. C. Tom, A. K. Katsaggelos, Reconstruction of a high-resolution image by simultaneous registration, restoration and interpolation of low-resolution images, Proceedings of the IEEE International Conference on Image Processing, Washington, DC, USA, pp.539C542, 1995.

R. C. Hardie, K. J. Barnard, E. E. Armstrong, Joint MAP registration and high-resolution image estimation using a sequence of undersampled images, IEEE Transactions on Image Processing, vol. 6, no. 12, pp. 1621 C 1633, 1997.

R. R. Schultz, R. L. Stevenson, Extraction of high-resolution frames from video sequences, IEEE Transactions on Image Processing,vol. 5, no. 6, pp. 996 C 1011, 1996.

M. Zibetti, F. Bazan, J. Mayer, Determining the regularization parameters for super-resolution problems, Signal Processing, vol.88, no. 12, pp. 2890C2901, 2008.

M. Zibetti, F. Bazan, J. Mayer, Estimation of the parameters in regularized simultaneous super-resolution, Pattern Recognition Letters, vol. 32, no. 1 pp. 69-78, 2011.

Z.Wang, Q. Zhang, X. Han, A. Hertzmann, C. E. Jacobs, N. Oliver, B. Curless, D. H. Salesin, Image analogies, Proceedings of the 28th annual conference on Computer graphics and interactive techniques, pp. 327 340, 2001.

J. Wang, S. Zhu, Y. Gong, Resolution enhancement based on learning the sparse association of image patches, Pattern Recognition Letters, vol. 31, no. 1, pp. 1C10, 2010.

K. I. Kim, Y. Kwon, Single-image super-resolution using sparse regression and natural image prior, IEEE transactions on pattern analysis & machine intelligence, vol. 32, no. 6, pp.1127C1133, 2010.

J. Yang, J. Wright, T. Huang, Y. Ma, Image super-resolution via sparse representation, IEEE Transactions on Image Processing,vol. 19, no. 11, pp. 2861 C 2873, 2010.

I. W. Selesnick, R. G. Baraniuk, N. G. Kingsbury, The Dual Tree Complex Wavelet Transform, IEEE Signal Process. Magazine vol.22, no. 6, pp. 123 - 151, 2005.

H. Demirel, G. Anbarjafari, Discrete Wavelet Transform-Based Satellite Image Resolution Enhancement, IEEE Transactions On Geoscience And Remote Sensing, vol. 49, no. 6, pp. 1997-2004, 2011.

H. Demirel, G. Anbarjafari, Satellite Image Resolution Enhancement Using Complex Wavelet Transform, IEEE Geoscience And Remote Sensing Letters, vol. 7, no. 1, pp. 123-126, 2010

Z. Iqbal, A. Ghafoor A. M. Siddiqui, Satellite Image Resolution Enhancement Using Dual-Tree Complex Wavelet Transform and Nonlocal Means, IEEE Geoscience And Remote Sensing Letters, vol. 10, no. 3 pp. 451 - 455, 2013.

S. Pertuz,D. Puig, M. A. Garcia,, Analysis of focus measure operators for shape-from-focus, Pattern Recognition, vol. 46, no. 5, pp.1415C1432, 2013.

Published
2018-11-02
How to Cite
Solanki, P., Israni, D., & Shah, A. (2018). An Efficient Satellite Image Super Resolution Technique for Shift-Variant Images using Improved New Edge Directed Interpolation. Statistics, Optimization & Information Computing, 6(4), 619-632. https://doi.org/10.19139/soic.v6i4.433
Section
Research Articles

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