A Novel Multispectral, Panchromatic and SAR Data Fusion for Land Classification

Multisensor data fusion is addressed in this article for land classification purposes in a semiarid environment. A novel algorithm based on multispectral, panchromatic and synthetic aperture radar (SAR) data is here presented. The proposed multisensory data fusion approach relies on the generalized intensity-hue-saturation (G-IHS) transform and the À trous wavelet transform (ATWT). The fusion product is obtained by modulating the high features details of the panchromatic ATWT with the SAR texture and by replacing the high-pass details of the G-IHS Intensity component with this panchromatic-SAR modulation. After the fusion product is derived, a classification is performed by using a standard maximum likelihood classifier. The proposed algorithm is tested over a meaningful case study acquired over the Maspalomas Special Natural Reserve (Spain) and processing data from WorldView-2 (for both multispectral and panchromatic channels) and TerraSAR-X (for the SAR channel) missions. Results show a fine preservation of the spectral information contained in each multispectral band. Sharpened details are observed over built-up areas and a smoothing texture is perceived over homogeneous areas (lakes, sea, bare soil, and roads) due to the SAR-panchromatic modulation. This leads to a better overall classification accuracy of the fused image compared to outcomes obtained with a single sensor, resulting 7% and 2% more accurate than multispectral and pan-sharpening classification, respectively.

[1]  E. Nezry,et al.  Adaptive speckle filters and scene heterogeneity , 1990 .

[2]  Beta Naught,et al.  Radiometric Calibration of TerraSAR-X Data , 2014 .

[3]  Robert M. Haralick,et al.  Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..

[4]  Kohji Fukunaga,et al.  Introduction to Statistical Pattern Recognition-Second Edition , 1990 .

[5]  Andreas Schenk,et al.  Delineation of Urban Footprints From TerraSAR-X Data by Analyzing Speckle Characteristics and Intensity Information , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[6]  Daniele Riccio,et al.  A New Classification Method for Semi-Arid Regions Based on SAR and LiDAR Data Fusion , 2019, IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium.

[7]  Lorenzo Bruzzone,et al.  A Special Issue on Big Data from Space for Geoscience and Remote Sensing [From the Guest Editors] , 2016 .

[8]  P. Dutilleux.  An Implementation of the “algorithme à trous” to Compute the Wavelet Transform , 1989 .

[9]  C. Padwick,et al.  WORLDVIEW-2 PAN-SHARPENING , 2010 .

[10]  Antonio Iodice,et al.  Flooding Water Depth Estimation With High-Resolution SAR , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[11]  Anthony Freeman,et al.  Radiometric correction and calibration of SAR images , 1989 .

[12]  F. Albregtsen.  Statistical Texture Measures Computed from Gray Level Coocurrence Matrices , 2008 .

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

[14]  Lorenzo Bruzzone,et al.  An unsupervised approach based on the generalized Gaussian model to automatic change detection in multitemporal SAR images , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[15]  Jong-Sen Lee,et al.  Digital Image Enhancement and Noise Filtering by Use of Local Statistics , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[16]  R. Chandrakanth,et al.  Feasibility of high resolution SAR and multispectral data fusion , 2011, 2011 IEEE International Geoscience and Remote Sensing Symposium.

[17]  Jie Chen,et al.  GA-SVM Algorithm for Improving Land-Cover Classification Using SAR and Optical Remote Sensing Data , 2017, IEEE Geoscience and Remote Sensing Letters.

[18]  Saeid Homayouni,et al.  MSMD: maximum separability and minimum dependency feature selection for cropland classification from optical and radar data , 2018 .

[19]  Luisa Verdoliva,et al.  SAR Image Despeckling by Soft Classification , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[20]  Wei Zhang,et al.  Multi-spectral and SAR images fusion via Mallat and À trous wavelet transform , 2010, 2010 18th International Conference on Geoinformatics.

[21]  Luciano Alparone,et al.  Landsat ETM+ and SAR image fusion based on generalized intensity Modulation , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[22]  E. Pottier,et al.  Polarimetric Radar Imaging: From Basics to Applications , 2009 .

[23]  Hannes Taubenböck,et al.  Investigation on the separability of slums by multi-aspect TerraSAR-X dual-co-polarized high resolution spotlight images based on the multi-scale evaluation of local distributions , 2018, Int. J. Appl. Earth Obs. Geoinformation.

[24]  Milan Sonka,et al.  Image Processing, Analysis and Machine Vision , 1993, Springer US.

[25]  Raffaella Guida,et al.  SAR, optical and LiDAR data fusion for the high resolution mapping of natural protected areas , 2015, 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[26]  Shuyuan Yang,et al.  Fusion of Multi-Sensor SAR Images via Adaptive Selection of Wavelet and Contourlet Coefficients , 2006, 2006 CIE International Conference on Radar.

[27]  Mark S. Nixon,et al.  Feature Extraction and Image Processing , 2002 .

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

[29]  Jun Li,et al.  Advanced Spectral Classifiers for Hyperspectral Images: A review , 2017, IEEE Geoscience and Remote Sensing Magazine.

[30]  I. Hajnsek,et al.  A tutorial on synthetic aperture radar , 2013, IEEE Geoscience and Remote Sensing Magazine.

[31]  Suman Deb,et al.  APPLICATION OF IMAGE FUSION FOR ENHANCING THE QUALITY OF AN IMAGE , 2012 .

[32]  Biao Hou,et al.  Using Combined Difference Image and $k$ -Means Clustering for SAR Image Change Detection , 2014, IEEE Geoscience and Remote Sensing Letters.

[33]  T. M. Lillesand,et al.  Remote Sensing and Image Interpretation , 1980 .

[34]  M. Herold,et al.  Fusing Landsat and SAR time series to detect deforestation in the tropics , 2015 .

[35]  Xiao Xiang Zhu,et al.  InSAR-BM3D: A Nonlocal Filter for SAR Interferometric Phase Restoration , 2018, IEEE Transactions on Geoscience and Remote Sensing.

[36]  Mihai Datcu,et al.  Multisensor Earth Observation Image Classification Based on a Multimodal Latent Dirichlet Allocation Model , 2018, IEEE Geoscience and Remote Sensing Letters.

[37]  Jocelyn Chanussot,et al.  A Critical Comparison Among Pansharpening Algorithms , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[38]  Firouz Abdullah Al-Wassai,et al.  The IHS Transformations Based Image Fusion , 2011, ArXiv.

[39]  Lei Wu,et al.  Remote Sensing Image Fusion Based on Adaptively Weighted Joint Detail Injection , 2018, IEEE Access.

[40]  T. M. Lillesand,et al.  Remote sensing and image interpretation. Second edition , 1987 .

[41]  Xiao Xiang Zhu,et al.  Data Fusion and Remote Sensing: An ever-growing relationship , 2016, IEEE Geoscience and Remote Sensing Magazine.

[42]  Jon Atli Benediktsson,et al.  Remote Sensing Data Fusion: Markov Models and Mathematical Morphology for Multisensor, Multiresolution, and Multiscale Image Classification , 2018 .

[43]  Zhenghao Shi,et al.  A comparison of digital speckle filters , 1994, Proceedings of IGARSS '94 - 1994 IEEE International Geoscience and Remote Sensing Symposium.

[44]  Biswajeet Pradhan,et al.  Fusion of Airborne LiDAR With Multispectral SPOT 5 Image for Enhancement of Feature Extraction Using Dempster–Shafer Theory , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[45]  Ujjwal Maulik,et al.  Remote Sensing Image Classification: A survey of support-vector-machine-based advanced techniques , 2017, IEEE Geoscience and Remote Sensing Magazine.