Satellite Dual-Polarization Radar Imagery Superresolution Under Physical Constraints

A novel physically justified method for spatial resolution enhancement of satellite dual-polarization synthetic aperture radar data is proposed. The method starts from the conversion of the specific land surface radar backscattering into the land surface dielectric permittivity in each polarization band separately. Said conversion is founded on a well-known integral equation model of synthetic aperture radar (SAR) backscattering. Transition from raw radar data to dielectric permittivity forms a common unified image field in each polarization band. Due to the SAR platform’s own movement, these fields are affected by some subpixel shift to each other. So, the opportunity to apply the superresolution technique over all permittivity fields at once is enabled with considering ones’ subpixel shift. Dual-image iterative superresolution based on Gaussian regularization was used. A standalone software module for statistical estimation of inter-images subpixel shift was developed earlier and applied in current research. A noticeable spatial resolution enhancement of the land surface dielectric permittivity field was achieved. This was demonstrated and quantified for actual dual-polarization radar images from the Sentinel-1 European SAR satellite system over two test sites in Ukraine.

[2]  Irene G. Karybali,et al.  An efficient spatial domain technique for subpixel image registration , 2008, Signal Process. Image Commun..

[3]  Moon Gi Kang,et al.  Super-resolution image reconstruction: a technical overview , 2003, IEEE Signal Process. Mag..

[4]  Selim Aksoy,et al.  Image classification and object detection using spatial contextual constraints , 2012 .

[5]  Elena Zaitseva,et al.  Multiple-Valued and Fuzzy Logics Application to Remote Sensing Data Analysis , 2018, 2018 26th Telecommunications Forum (TELFOR).

[6]  Antonio Iodice,et al.  Sentinel-1 for Monitoring Reservoirs: A Performance Analysis , 2014, Remote. Sens..

[7]  Joonki Paik,et al.  Multisensor Super Resolution Using Directionally-Adaptive Regularization for UAV Images , 2015, Sensors.

[8]  Richard K. Moore,et al.  Microwave Remote Sensing, Active and Passive , 1982 .

[9]  Sergey A. Stankevich,et al.  Subpixel resolution satellite imaging technique , 2013, The International Conference on Digital Technologies 2013.

[10]  Nicolas Brodu,et al.  Super-Resolving Multiresolution Images With Band-Independent Geometry of Multispectral Pixels , 2016, IEEE Transactions on Geoscience and Remote Sensing.

[11]  M. S. Lubskyi,et al.  Leaf area index estimation of forest using sentinel-1 C-band SAR data , 2017, 2017 IEEE Microwaves, Radar and Remote Sensing Symposium (MRRS).

[12]  V. Zatyagalova,et al.  APPLICATION OF ENVISAT SAR IMAGERY FOR MAPPING AND ESTIMATION OF NATURAL OIL SEEPS IN THE SOUTH CASPIAN SEA , 2007 .

[13]  H Stark,et al.  High-resolution image recovery from image-plane arrays, using convex projections. , 1989, Journal of the Optical Society of America. A, Optics and image science.

[14]  Warren B. Cohen,et al.  Automated designation of tie-points for image-to-image coregistration , 2003 .

[15]  Dirk Geudtner,et al.  Sentinel-1 system overview and performance , 2012, 2012 IEEE International Geoscience and Remote Sensing Symposium.

[16]  Hong Zhu,et al.  Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement , 2018, Sensors.

[17]  J. C. Dainty,et al.  Iterative blind deconvolution method and its applications , 1988 .

[18]  Kamal Sarabandi,et al.  Microwave Radar and Radiometric Remote Sensing , 2013 .

[19]  Martin Vetterli,et al.  Subspace-based methods for image registration and super-resolution , 2008, 2008 15th IEEE International Conference on Image Processing.

[20]  Hongquan Wang Soil Moisture Retrieval from Microwave Remote Sensing Observations , 2018, Soil Moisture.

[21]  James Brusey,et al.  An Event-Triggered Machine Learning Approach for Accelerometer-Based Fall Detection , 2017, Sensors.

[22]  Yu Liu,et al.  A framework of region-based spatial relations for non-overlapping features and its application in object based image analysis , 2008 .

[23]  A. Papoulis A new algorithm in spectral analysis and band-limited extrapolation. , 1975 .

[24]  Michael T. Orchard,et al.  A fast direct Fourier-based algorithm for subpixel registration of images , 2001, IEEE Trans. Geosci. Remote. Sens..

[25]  C Chen,et al.  Signal and Image Processing for Remote Sensing, Second Edition , 2012 .

[26]  Timothy M. Kusky,et al.  Structural controls on Neoproterozoic mineralization in the South Eastern Desert, Egypt: an integrated field, Landsat TM, and SIR-C/X SAR approach , 2002 .

[27]  Shree K. Nayar,et al.  Video super-resolution using controlled subpixel detector shifts , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[28]  Pao-Chi Chang,et al.  Imaging Simulation for Synthetic Aperture Radar: A Full-Wave Approach , 2018, Remote. Sens..

[29]  Ming Hu,et al.  A Novel Controller Design for the Next Generation Space Electrostatic Accelerometer Based on Disturbance Observation and Rejection , 2016, Sensors.

[30]  S. Susan Young,et al.  Signal Processing and Performance Analysis for Imaging Systems , 2008 .

[31]  V. N. Podorvan,et al.  Thermal infrared imagery informativity enhancement using sub-pixel co-registration , 2016, 2016 International Conference on Information and Digital Technologies (IDT).

[32]  Song Ji,et al.  STUDY ON THE METHODS OF SUPER-RESOLUTION IMAGE RECONSTRUCTION , 2007 .

[33]  Sergey V. Shklyar,et al.  Software module for estimating subpixel shift of images acquired from quadcopter , 2018 .

[34]  Wenzhong Shi,et al.  Remote Sensing Image Classification Based on Stacked Denoising Autoencoder , 2017, Remote. Sens..

[35]  R. Gerchberg Super-resolution through Error Energy Reduction , 1974 .

[36]  Qi Gao,et al.  Synergetic Use of Sentinel-1 and Sentinel-2 Data for Soil Moisture Mapping at 100 m Resolution , 2017, Sensors.

[37]  Peyman Milanfar,et al.  A wavelet-based interpolation-restoration method for superresolution (wavelet superresolution) , 2000 .

[38]  Josiane Zerubia,et al.  Subpixel image registration by estimating the polyphase decomposition of cross power spectrum , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.