A New Variational Model for Panchromatic and Multispectral Image Fusion
-
摘要: 图像融合是提供包含各输入图像互补信息的单幅图像的有力工具. 本文提出了一种新的用于全色和多光谱图像融合的变分模型. 在Socolinsky对比度模型的基础上构造了一个改进的能量泛函最小化问题, 以寻找最接近全色图像梯度的解.为了提高多光谱图像的空间分辨率,并尽可能地保持其原有的光谱信息, 还将光谱一致项、波段间相关项和对比度增强项引入融合模型. 在IKONOS和QuickBird数据集上测试了该模型的性能.实验结果表明该模型可以生成同时具有高空间质量和高光谱质量的融合图像.Abstract: Image fusion is a powerful tool to provide a single image which contains the complementary information from the input images. A novel variational model is presented for panchromatic and multispectral image fusion. Based on the Socolinsky's contrast model, an advanced energy minimization problem is posed to find the solution whose gradient is closest to that of the panchromatic image. To improve the multispectral image's spatial resolution and preserve its spectral information as much as possible, spectral coherence, interband correlation and contrast enhancement terms are explicitly enforced into the fusion process. The performance of our model is evaluated on several IKONOS and QuickBird datasets. Experimental results show that our model can produce images with both high spatial and high spectral quality.
-
Key words:
- Image fusion /
- variation /
- energy functional /
- spectral coherence /
- IKONOS /
- QuickBird
-
[1] Carper W J, Lillesand T M, Kiefer R W. The use of intensity-hue-saturation transformations for merging SPOT panchromatic and multi-spectral image data. Photogrammetric Engineering and Remote Sensing, 1990, 56(4): 459-467[2] Chavez P S Jr, Sides S C, Anderson J A. Comparison of three different methods to merge multiresolution and multispectral data: Landsat TM and SPOT panchromatic. Photogrammetric Engineering and Remote Sensing, 1991, 57(3): 295-303[3] Tu T M, Huang P S, Hung C L, Chang C P. A fast intensity-hue-saturation fusion technique with spectral adjustment for IKONOS imagery. IEEE Geoscience and Remote Sensing Letters, 2004, 1(4): 309-312[4] Chavez P S Jr, Kwarteng A Y. Extracting spectral contrast in Landsat thematic mapper image data using selective principal component analysis. Photogrammetric Engineering and Remote Sensing, 1989, 55(3): 339-348[5] González-Audícana M, Saleta J L, Catalán R G, García R. Fusion of multispectral and panchromatic images using improved IHS and PCA mergers based on wavelet decomposition. IEEE Transactions on Geoscience and Remote Sensing, 2004, 42(6): 1291-1299[6] Civco D L, Wang Y, Silander J A. Characterizing forest ecosystems in connecticut by integrating Landsat TM and SPOT panchromatic data. In: Proceedings of the 1995 Annual Convention and Exploration. Charlotte, USA: ASPRS/ACSM, 1995. 216-224[7] Zhou J, Civco D L, Silander J A. A wavelet transform method to merge Landsat TM and SPOT panchromatic data. International Journal of Remote Sensing, 1998, 19(4): 743-757[8] Shettigara V K. A generalized component substitution technique for spatial enhancement of multispectral images using a higher resolution data set. Photogrammetric Engineering and Remote Sensing, 1992, 58(5): 561-567[9] Laben C A, Brower B V. Process for Enhancing the Spatial Resolution of Multispectral Imagery Using Pan-Sharpening, U.S. Patent 6011875, January 2000[10] Aiazzi B, Baronti S, Selva M. Improving component substitution pansharpening through multivariate regression of MS + Pan data. IEEE Transactions on Geoscience and Remote Sensing, 2007, 45(10): 3230-3239[11] Zhang Y, Hong G. An IHS and wavelet integrated approach to improve pan-sharpening visual quality of natural colour IKONOS and QuickBird images. Information Fusion, 2005, 6(3): 225-234[12] Chen T, Zhang J P, Zhang Y. Remote sensing image fusion based on ridgelet transform. In: Proceedings of the 2005 IEEE International Geoscience and Remote Sensing Symposium. Seoul, South Korea: IEEE, 2005. 1150-1153[13] Choi M, Kim R Y, Nam M R, Kim H O. Fusion of multispectral and panchromatic satellite images using the curvelet transform. IEEE Geoscience and Remote Sensing Letters, 2005, 2(2): 136-140[14] Nencini F, Garzelli A, Baronti S, Alparone L. Remote sensing image fusion using the curvelet transform. Information Fusion, 2007, 8(2): 143-156[15] Yang Xiao-Hui, Jiao Li-Cheng. Fusion algorithm for remote sensing images based on nonsubsampled contourlet transform. Acta Automatica Sinica, 2008, 34(3): 274-281 (杨晓慧, 焦李成. 基于非子采样Contourlet变换的遥感图像融合算法. 自动化学报. 2008, 34(3): 274-281)[16] Ballester C, Caselles V, Igual L, Verdera J, Rougé B. A variational model for P+XS image fusion. International Journal of Computer Vision, 2006, 69(1): 43-58[17] Moeller M, Wittman T, Bertozzi A L. A variational approach to hyperspectral image fusion. In: Proceedings of Algorithms and Technologies for Multispectral, Hyperspectral and Ultraspectral Imagery XV. Orlando, USA: SPIE, 2009. 73341E-73341E-10[18] Socolinsky D A, Wolff L B. Multispectral image visualization through first-order fusion. IEEE Transactions on Image Processing, 2002, 11(8): 923-931[19] Piella G. Image fusion for enhanced visualization: a variational approach. International Journal of Computer Vision, 2009, 83(1): 1-11[20] Bertalmío M, Caselles V, Provenzi E, Rizzi A. Perceptual color correction through variational techniques. IEEE Transactions on Image Processing, 2007, 16(4): 1058-1072[21] Wang W W, Shui P L, Feng X C. Variational models for fusion and denoising of multifocus images. IEEE Signal Processing Letters, 2008, 15(1): 65-68[22] Yuhas R H, Goetz F H A, Boardman J W. Discrimination among semiarid landscape endmembers using the spectral angle mapper (SAM) algorithm. In: Proceedings of the 1992 Summaries of the 3rd Annual JPL Airborne Geoscience Workshop. Pasadena, USA: JPL, 1992. 147-149[23] Sapiro G, Caselles V. Histogram modification via differential equations. Journal of Differential Equations, 1997, 135(2): 238-268[24] Ranchin T, Aiazzi B, Alparone L, Baronti S, Wald L. Image fusion-the ARSIS concept and some successful implementation schemes. ISPRS Journal of Photogrammetry and Remote Sensing, 2003, 58(1-2): 4-18[25] Wang Z, Bovik A C. A universal image quality index. IEEE Signal Processing Letters, 2002, 9(3): 81-84
点击查看大图
计量
- 文章访问数: 1509
- HTML全文浏览量: 57
- PDF下载量: 1029
- 被引次数: 0