Multiscale Image Fusion Using the Undecimated Wavelet Transform With Spectral Factorization and Nonorthogonal Filter Banks

Multiscale transforms are among the most popular techniques in the field of pixel-level image fusion. However, the fusion performance of these methods often deteriorates for images derived from different sensor modalities. In this paper, we demonstrate that for such images, results can be improved using a novel undecimated wavelet transform (UWT)-based fusion scheme, which splits the image decomposition process into two successive filtering operations using spectral factorization of the analysis filters. The actual fusion takes place after convolution with the first filter pair. Its significantly smaller support size leads to the minimization of the unwanted spreading of coefficient values around overlapping image singularities. This usually complicates the feature selection process and may lead to the introduction of reconstruction errors in the fused image. Moreover, we will show that the nonsubsampled nature of the UWT allows the design of nonorthogonal filter banks, which are more robust to artifacts introduced during fusion, additionally improving the obtained results. The combination of these techniques leads to a fusion framework, which provides clear advantages over traditional multiscale fusion approaches, independent of the underlying fusion rule, and reduces unwanted side effects such as ringing artifacts in the fused reconstruction.

[1]  Peter J. Burt,et al.  Enhanced image capture through fusion , 1993, 1993 (4th) International Conference on Computer Vision.

[2]  Oliver Rockinger,et al.  Image sequence fusion using a shift-invariant wavelet transform , 1997, Proceedings of International Conference on Image Processing.

[3]  Shutao Li,et al.  Performance comparison of different multi-resolution transforms for image fusion , 2011, Inf. Fusion.

[4]  N. Kingsbury Complex Wavelets for Shift Invariant Analysis and Filtering of Signals , 2001 .

[5]  Vladimir Petrovic,et al.  Objective image fusion performance measure , 2000 .

[6]  Nikolaos Mitianoudis,et al.  Pixel-based and region-based image fusion schemes using ICA bases , 2007, Inf. Fusion.

[7]  Rick S. Blum,et al.  A categorization of multiscale-decomposition-based image fusion schemes with a performance study for a digital camera application , 1999, Proc. IEEE.

[8]  G. Qu,et al.  Information measure for performance of image fusion , 2002 .

[9]  M. Do Directional multiresolution image representations , 2002 .

[10]  Cedric Nishan Canagarajah,et al.  Pixel- and region-based image fusion with complex wavelets , 2007, Inf. Fusion.

[11]  Myeong-Ryong Nam,et al.  Fusion of multispectral and panchromatic Satellite images using the curvelet transform , 2005, IEEE Geoscience and Remote Sensing Letters.

[12]  Gonzalo Pajares,et al.  A wavelet-based image fusion tutorial , 2004, Pattern Recognit..

[13]  Shutao Li,et al.  Image Fusion Using Nonsubsampled Contourlet Transform , 2007, Fourth International Conference on Image and Graphics (ICIG 2007).

[14]  Vladimir S. Petrovic,et al.  Subjective tests for image fusion evaluation and objective metric validation , 2007, Inf. Fusion.

[15]  Zheng Liu,et al.  Image fusion by using steerable pyramid , 2001, Pattern Recognit. Lett..

[16]  Mrityunjay Kumar,et al.  A Total Variation-Based Algorithm for Pixel-Level Image Fusion , 2009, IEEE Transactions on Image Processing.

[17]  Stéphane Mallat,et al.  A Wavelet Tour of Signal Processing - The Sparse Way, 3rd Edition , 2008 .

[18]  Mohamed-Jalal Fadili,et al.  The Undecimated Wavelet Decomposition and its Reconstruction , 2007, IEEE Transactions on Image Processing.

[19]  Andrea Garzelli,et al.  Context-driven fusion of high spatial and spectral resolution images based on oversampled multiresolution analysis , 2002, IEEE Trans. Geosci. Remote. Sens..

[20]  Luciano Alparone,et al.  Remote sensing image fusion using the curvelet transform , 2007, Inf. Fusion.

[21]  Zheng Liu,et al.  Objective Assessment of Multiresolution Image Fusion Algorithms for Context Enhancement in Night Vision: A Comparative Study , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[22]  Alexander Toet,et al.  Image fusion by a ration of low-pass pyramid , 1989, Pattern Recognit. Lett..

[23]  Henk J. A. M. Heijmans,et al.  A new quality metric for image fusion , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[24]  Mark J. Shensa,et al.  The discrete wavelet transform: wedding the a trous and Mallat algorithms , 1992, IEEE Trans. Signal Process..

[25]  L.A. Ray,et al.  Dual tree discrete wavelet transform with application to image fusion , 2006, 2006 Proceeding of the Thirty-Eighth Southeastern Symposium on System Theory.

[26]  Vladimir S. Petrovic,et al.  Gradient-based multiresolution image fusion , 2004, IEEE Transactions on Image Processing.

[27]  Shutao Li,et al.  Hybrid Multiresolution Method for Multisensor Multimodal Image Fusion , 2010, IEEE Sensors Journal.

[28]  B. S. Manjunath,et al.  Multisensor Image Fusion Using the Wavelet Transform , 1995, CVGIP Graph. Model. Image Process..

[29]  Gemma Piella,et al.  Adaptive wavelets and their applications to image fusion and compression , 2003 .

[30]  Martin Vetterli,et al.  Oversampled filter banks , 1998, IEEE Trans. Signal Process..

[31]  Richard Baraniuk,et al.  The Dual-tree Complex Wavelet Transform , 2007 .

[32]  Amrane Houacine,et al.  Redundant versus orthogonal wavelet decomposition for multisensor image fusion , 2003, Pattern Recognit..

[33]  Minh N. Do,et al.  The Nonsubsampled Contourlet Transform: Theory, Design, and Applications , 2006, IEEE Transactions on Image Processing.

[34]  Xavier Otazu,et al.  Multiresolution-based image fusion with additive wavelet decomposition , 1999, IEEE Trans. Geosci. Remote. Sens..

[35]  Shuyuan Yang,et al.  Image fusion based on a new contourlet packet , 2010, Inf. Fusion.

[36]  M. Farooq,et al.  A real time pixel-level based image fusion via adaptive weight averaging , 2000, Proceedings of the Third International Conference on Information Fusion.

[37]  B. Luo,et al.  Large-Scale Graph Database Indexing Based on T-mixture Model and ICA , 2007, Fourth International Conference on Image and Graphics (ICIG 2007).

[38]  P. J. Burt,et al.  The Pyramid as a Structure for Efficient Computation , 1984 .

[39]  Qiang Zhang,et al.  Multifocus image fusion using the nonsubsampled contourlet transform , 2009, Signal Process..