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Application of improved Welsh’s color transfer algorithm to GF-2 image fusion |
| YIN Feng1, CAO Liqin2, Liang Peng1 |
1. Hubei Provincial Department of Land and Resources, Wuhan 430071, China;
2. School of Printing and Packaging, Wuhan University, Wuhan 430079, China |
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Abstract During the processing, image fusion, calibration, registration and other pre-processing steps for images are onerous tasks in land resources investigation. In this paper, the improved Welsh color transfer was proposed for image fusion. The study area was Xiantao City in Hubei Province and the study images were GF-2 high spatial resolution image data. The result of color-based image fusion algorithm was qualitatively and quantitatively compared with that of Gram-Schmidt(GS)and principal components(PC) fusion methods. The results show that the improved Welsh color transfer has good performance on preserving color fidelity and texture similarity. Especially in complex land-surface areas, the texture similarity of result image based on improved color transfer method is much better than that based on GS and PC fusion algorithm. The color transfer method is also applied to images fusion about different areas without calibration and registration for images.
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| Keywords
remote sensing
coal mine
subsidence
restoration and management
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Issue Date: 04 December 2017
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[1] Al-Wassai F A,Kalyankar N V,Al-Zuky A A.The IHS transformations based image fusion[J].International Journal of Advanced Research in Computer Science,2011,2(5):1-10.
[2] Ehlers M,Klonus S,?strand P J,et al.Multi-sensor image fusion for pansharpening in remote sensing[J].International Journal of Image and Data Fusion,2010,1(1):25-45.
[3] Joshi M V,Bruzzone L,Chaudhuri S.A model-based approach to multiresolution fusion in remotely sensed images[J].IEEE Transactions on Geoscience and Remote Sensing,2006,44(9):2549-2562.
[4] Cetin M,Musaoglu N.Merging hyperspectral and panchromatic image data:Qualitative and quantitative analysis[J].International Journal of Remote Sensing,2009,30(7):1779-1804.
[5] 刘会芬,杨英宝,于 双,等.遥感图像不同融合方法的适应性评价——以ZY-3和Landsat8图像为例[J].国土资源遥感,2014,26(4):63-70.doi:10.6046/gtzyyg.2014.04.11.
Liu H F,Yang Y B,Yu S,et al.Adaptability evaluation of different fusion methods on ZY-3 and Landsat8 images[J].Remote Sensing for Land and Resources,2014,26(4):63-70.doi:10.6046/gtzyyg.2014.04.11.
[6] Reinhard E,Adhikhmin M,Gooch B,et al.Color transfer between images[J].IEEE Computer Graphics and Applications,2001,21(5):34-41.
[7] Welsh T,Ashikhmin M,Mueller K.Transferring color to greyscale images[J].ACM Transactions on Graphics,2002,21(3):277-280.
[8] 向 遥.基于视觉感知的图像处理方法研究[D].长沙:中南大学,2011.
Xiang Y.Image Processing Methods Based on Human Visual Perception[D].Changsha:Central South University,2011.
[9] 谢相建,赵俊三,陈学辉,等.基于集对分析的遥感图像K-均值聚类算法[J].国土资源遥感,2012,24(4):82-87.doi:10.6046/gtzyyg.2012.04.14.
Xie X J,Zhao J S,Chen X H,et al.SPA-based K-means clustering algorithm for remote sensing image[J].Remote Sensing for Land and Resources,2012,24(4):82-87.doi:10.6046/gtzyyg.2012.04.14.
[10] Hasler D,Suesstrunk S E.Measuring colorfulness in natural images[C]//Proceedings of the SPIE 5007,human vision and electronic imaging VIII.Santa Clara,CA,USA:SPIE,2003,5007:87-95.
[11] 陈恩生.基于图像相似度的颜色迁移方法研究[D].武汉:武汉大学,2013.
Chen E S.Research on Color Transfer Based on Image Similarity[D].Wuhan:Wuhan University,2013.
[12] Wang Z,Bovik A C,Sheikh H R,et al.Image quality assessment:From error visibility to structural similarity[J].IEEE Transactions on Image Processing,2004,13(4):600-612. |
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2017,
Vol. 29
