Multisource remote sensing image fusion based on curvelet and wavelet transform
Aiming at limitations of existing multiresolution analysis (MRA) fusion methods, this paper proposes a new fusion method which combines curvelet and wavelet transform. Curvelet transform processes edges better than wavelet transform does. While wavelet transform handles smooth area better than curvelet transform does. As an image often includes more than one feature, the proposed method is conducted on the basis of region segmentation and use àtrous wavelet transform (ATWT) to fuse smooth areas and fast discrete curvelet transform (FDCT) to fuse areas with edges. Furthermore, an optimal objective function defined based on a balance between spectral preservation and spatial resolution improvement is put forward to search optimal segmentation threshold. The optimal fusion result can be obtained by fusion processing through the optimal segmentation threshold. Landsat TM multispectral (MS) images and SPOT Panchromatic (Pan) image covering a region of Wuhan in Hubei province are tested to assess this proposed method. Visual evaluation and statistics analysis are employed to assess the quality of fused images of different methods. The proposed method demonstrates best results among methods being tested in this study. So by combining attributes of both transforms, it is possible to get better image fusion result than by using wavelet and curvelet individually.
Multispectral (MS) image Panchromatic (Pan) image remote sensing wavelet transform curvelet transform multiresolution analysis (MRA) region segmentation image fusion
Moyan Xiao Zhibiao He
College of Mathematics and Econometrics, Hubei University of Education,2nd Guanggu Road No.29, Wuhan GNSS ,Wuhan University,129 Loyu Road, Wuhan 430079, P.R. China
国际会议
桂林
英文
1-6
2011-11-01（万方平台首次上网日期，不代表论文的发表时间）