Efficient Hybrid Method for Pan-Sharpening Enhancement of Multiband Satellite Images | ||||
| Menoufia Journal of Electronic Engineering Research | ||||
| Article 3, Volume 29, Issue 1, January 2020, Page 21-30 PDF (1.52 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/mjeer.2020.69011 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Tamer M. Talal1; Gamal Attiya 2; Mohamed R. Metwalli3; Fathi E. Abd El-Samie4; M.I. Dessouky5
| ||||
| 1Dept. of Space National Authority for Remote Sensing and Space Sciences (NARSS) Cairo, Egypt | ||||
| 2Dept. of Computer Science and Engineering Faculty of Electronic Engineeing, Menofia University Menouf, Egypt | ||||
| 3Dept. of Data reception National Authority for Remote Sensing and Space Sciences (NARSS) Cairo, Egypt | ||||
| 4Dept. of Communications Faculty of Electronic Engineeing, Menofia University Menouf, Egypt | ||||
| 5Dept. of Communications Faculty of Electronic Engineeing, Menofia University | ||||
| Abstract | ||||
| Pan-sharpening considers one of the most important applications for satellite images as it enhances spectral and spatial information for the images. Empirical Mode Decomposition (EMD) is one of the most powerful techniques for pan-sharpening. It first decomposes the image into a set of Intrinsic Mode Functions (IMFs) and a residual component. These panchromatic and multispectral components are then fused to create an enhanced pan-sharpened image. This paper presents an efficient hybrid method for enhancing pan-sharpening of multiband images transmitted from satellite to ground stations. The proposed approach combines this EMD technique with the most powerful conventional method; Discrete Wavelet Transform (DWT), to maximize the pan-sharpening gain. The proposed hybrid method is validated using satellite images of Nile Valley and Suez Canal region, Egypt, captured by Spot-4 and Landsat-8 satellites. The results imply that the proposed hybrid method provides better qualitative and quantitative quality comparing with the individual and the most common pan-sharpening methods. | ||||
| Keywords | ||||
| DWT; EMD; image fusion; Landsat-8; pan-sharpening; and Spot-4 | ||||
| References | ||||
|
[1] L. Wald, “Some terms of reference in data fusion,” IEEE Trans. on Geoscience and Remote Sensing, vol. 37, no. 3, pp. 1190–1193, May 1999. [2] Z. Wang, D. Ziou, C. Armenakis, D. Li, and Q. Li, “A comparative analysis of image fusion methods” IEEE Trans. on Geoscience and Remote Sensing, vol. 43, no. 6, pp. 1391–1402, June 2005. [3] Z Li, J Chen, E Baltsavias, “Advances in Photogrammetry”, Remote Sensing and Spatial Information Sciences: ISPRS Congress Book, Taylar & Francis Group, 2008. [4] R. A. Schowengerdt, “Remote Sensing: Models and Methods for Image Processing”, 2nd edition Orlando, FL: Academic, 1997. [5] T. Ranchin and L. Wald, “Fusion of high spatial and spectral resolution images: The ARSIS concept and its implementation,” Photogrammetry Engineering Remote Sensing, vol. 66, no. 1, pp. 49–61, 2000. [6] B. Aiazzi, S. Baronti, and M. Selva, “Improving component substitution pan-sharpening through multivariate regression of MS+Pan Data”, IEEE Trans. on Geoscience and Remote Sensing, vol. 45, no. 10, October 2007. [7] S. S. Han, H. T. Li, and H. Y. Gu, “The study on image fusion for high spatial resolution remote sensing images”, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. vol. XXXVII. part B7, pp. 1159–1164, Beijing, 2008. [8] J. G. Liu, “Smoothing filter-based intensity modulation: A spectral preserve image fusion technique for improving spatial details,” Journal of Remote Sensing, vol. 21, no. 18, pp. 3461–3472, 2000. [9] H. Liu, and X. Zhang, “Comparison of data fusion techniques for Beijing-1 micro-satellite images”, Urban Remote Sensing Joint Event, IEEE, 2009. [10] S.de Béthune, F. Muller, and J. P. Donnay, “Fusion of multi-spectral and panchromatic images by local mean and variance matching filtering techniques,” Fusion of Earth Data Conf., Jan. 28–30, 1998. [11] B. Aiazzi, L. Alparone, S. Baronti, and A. Garzelli, “Context-driven fusion of high spatial and spectral resolution images based on oversampled multi-resolution analysis,” IEEE Trans. On Geoscience Remote Sensing, vol. 40, no. 10, pp. 2300–2312, Oct. 2002. [12] H. Ghassemian, “A review of remote sensing image fusion methods”, Journal of Information Fusion, Vol. 32, Part A, pp. 75-89, Nov. 2016. [13] H. Hariharan, A. Gribok, M. Abidi, and A. Koschan, "Image Fusion and Enhancement via Empirical Mode Decomposition," Journal of Pattern Recognition Research, vol. 1, no. 1, pp. 16-32, January 2006. [1] T. A. Teo and C. C. Lau,” Pyramid-Based Image Empirical Mode Decomposition for the Fusion of Multispectral and Panchromatic Images”, EURASIP Journal on Advances in Signal Processing, 2012. [2] S. Chen, y. Su, R. Zhang, and J. Tian, “ Fusing Remote Sensing Images using a Trous Wavelet Transform and Empirical Mode Decomposition.”, Pattern Recognition Letter, vol.29, 330–342, 2008. [3] B. Demir, S. Ertürk and M. K. Güllü, " Empirical Mode Decomposition of Hyperspectral Images for Support Vector Machine Classification, " IEEE Trans. On Geoscience and Remote Sensing letters, Vol. 8, No. 2, pp. 4071-4084, March. 201l. [4] E. T. Gormas, N. Canagaraiah and A. Achim," Dimensionality Reduction of Hyperspectral images using Empirical Mode Decomposition and Wavelets, " IEEE Journal of Selected Topics in Applied Earth observations and Remote sensing, Vol. 5, No. 6, pp. 1821-1830, Dec. 2012. [5] S. Lahmiri and M. Boukadoum, "A Weighted Bio-signal Denoising Approach Using Empirical Mode Decomposition," Biomed. Eng.Letter , Vol.5, pp. 131-139, 2015. [6] M. R. Metwalli. , “Assessing the quality of satellite images using advanced data fusion techniques”, Ph.D. thesis in Electronic Engineering, Menofia University, Egypt, 2012. [7] Z. Wang, and A. C. Bovik, “A Universal Image Quality Index," IEEE Signal Processing Letter, vol. 9, no. 3, pp. 81-84, 2002. [8] P. S. Pradhan, R. L. King, N. H. Younan, and D. W. Holcomb, “Estimation of The Number of Decomposition Levels for a Wavelet-Based Multiresolution Multisensor Image Fusion," IEEE Transactions on Geoscience and Remote Sensing, Vol. 44, No. 12, pp. 3674-3686, 2006. [9] J. Zhou, D.L. Civco, and J.A. Silander, “A wavelet transform method to merge Landsat TM and SPOT panchromatic data,” International Journal of Remote Sensing, vol.19, no.4, pp.743-757, 1998. | ||||
|
Statistics Article View: 223 PDF Download: 168 |
||||
