A New DCT-based Multiresolution Method for Simultaneous Denoising and Fusion of SAR Images

Individual multiresolution techniques for separate image fusion and denoising have been widely researched. We propose a novel multiresolution discrete cosine transform based method for simultaneous image denoising and fusion, demonstrating its efficacy with respect to discrete wavelet transform and dual-tree complex wavelet transform. We incorporate the Laplacian pyramid transform multiresolution analysis and a sliding window discrete cosine transform for simultaneous denoising and fusion of the multiresolution coefficients. The impact of image denoising on the results of fusion is demonstrated and advantages of simultaneous denoising and fusion for SAR images are also presented

[1]  Jaakko Astola,et al.  Transform Based Denoising Algorithms: Comparative Study , 2022 .

[2]  Fawwaz T. Ulaby,et al.  Statistical properties of logarithmically transformed speckle , 2002, IEEE Trans. Geosci. Remote. Sens..

[3]  S. Sanjeevi,et al.  COMPARISON OF CONVENTIONAL AND WAVELET TRANSFORM TECHNIQUES FOR FUSION OF IRS-1C LISS-III AND PAN IMAGES , 2001 .

[4]  Dan Ionescu,et al.  A Kalman filter with state multiplicative noise for SAR data , 1995, 1995 International Geoscience and Remote Sensing Symposium, IGARSS '95. Quantitative Remote Sensing for Science and Applications.

[5]  D. Capstick,et al.  The effects of speckle reduction on classification of ERS SAR data , 2001 .

[6]  Mieczyslaw M. Kokar,et al.  Multiresolutional multisensor target identification , 1994, Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems.

[7]  Tao Mei,et al.  Improved multiscale image enhancement via Laplacian pyramid , 2002, Other Conferences.

[8]  Edward H. Adelson,et al.  The Laplacian Pyramid as a Compact Image Code , 1983, IEEE Trans. Commun..

[9]  Mongi A. Abidi,et al.  A Combinational Approach to the Fusion, De-noising and Enhancement of Dual-Energy X-Ray Luggage Images , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops.

[10]  Dmitri Loguinov,et al.  Bayesian wavelet shrinkage with edge detection for SAR image despeckling , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[11]  Peng-Lang Shui,et al.  Multifocus image fusion in wavelet domain , 2003, Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693).

[12]  N. Kingsbury.  Image processing with complex wavelets , 1999, Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[13]  John C. Curlander,et al.  Synthetic Aperture Radar: Systems and Signal Processing , 1991 .

[14]  Jaakko Astola,et al.  Transform domain image restoration methods: review, comparison, and interpretation , 2001, IS&T/SPIE Electronic Imaging.

[15]  Fawwaz T. Ulaby,et al.  SAR speckle reduction using wavelet denoising and Markov random field modeling , 2002, IEEE Trans. Geosci. Remote. Sens..

[16]  I. Daubechies.  Ten Lectures on Wavelets , 1992 .

[17]  Ian G. Cumming,et al.  Bayesian speckle noise reduction using the discrete wavelet transform , 1998, IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174).

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

[19]  Karen O. Egiazarian,et al.  Signal and image denoising in transform domain and wavelet shrinkage: A comparative study , 1998, 9th European Signal Processing Conference (EUSIPCO 1998).

[20]  Vladimir V. Lukin,et al.  Local transform-based denoising for radar image processing , 2001, IS&T/SPIE Electronic Imaging.

[21]  Firooz Sadjadi,et al.  Comparative Image Fusion Analysais , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops.

[22]  G..  A Theory for Multiresolution Signal Decomposition : The Wavelet Representation , 2004 .

[23]  Koen C. Mertens,et al.  WAVELET-BASED FUSION OF SPOT/VEGETATION AND ENVISAT/ ASAR WIDE SWATH DATA FOR WETLAND MAPPING , 2004 .

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

[25]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[26]  Jing Li,et al.  A detail-preserving and flexible adaptive filter for speckle suppression in SAR imagery , 2003 .

[27]  G. Piella.  New quality measures for image fusion , 2004 .

[28]  Leonid P. Yaroslavsky,et al.  Local adaptive image restoration and enhancement with the use of DFT and DCT in a running window , 1996, Optics & Photonics.