scholarly journals Automated SAR Image Thresholds for Water Mask Production in Alberta’s Boreal Region

2020 ◽  
Vol 12 (14) ◽  
pp. 2223
Author(s):  
Craig Mahoney ◽  
Michael Merchant ◽  
Lyle Boychuk ◽  
Chris Hopkinson ◽  
Brian Brisco
Keyword(s):  
Surface Water ◽  
Synthetic Aperture Radar ◽  
Large Scale ◽  
Synthetic Aperture ◽  
Threshold Selection ◽  
Anthropogenic Pressures ◽  
Novel Method ◽  
Water Mapping ◽  
Sar Imagery ◽  
Aperture Radar

Mapping and monitoring surface water features is important for sustainably managing this critical natural resource that is in decline due to numerous natural and anthropogenic pressures. Satellite Synthetic Aperture Radar is a popular and inexpensive solution for such exercises over large scales through the application of thresholds to distinguish water from non-water. Despite improvements to threshold methods, threshold selection is traditionally manual, which introduces subjectivity and inconsistency over large scales. This study presents a novel method for objectively determining and applying a threshold to determine water masks from Synthetic Aperture Radar (SAR) imagery on a scene-by-scene basis. The method was applied to Radarsat-2 and simulated Radarsat Constellation Mission scenes, and validated against two independent validation sources with high accuracy (Kappa ranging from 0.85 to 0.93). Expectedly, greatest misclassification occurs near shorelines, which are often ecologically important zones. Comparisons between Radarsat-2 and Radarsat Constellation Mission thresholds and outputs suggest that the latter is a capable successor for surface water applications. This work represents a foundational step toward objectivity and consistency in large-scale water mapping and monitoring.

scholarly journals RASF and DEDR-POCS Image Fusion through Multi-layer Perceptron in SAR Imagery Systems

2019 ◽  
pp. 20-26
Author(s):  
Israel Yañez-Vargas ◽  
Joel Quintanilla-Domínguez ◽  
Gabriel Aguilera-Gonzalez
Keyword(s):  
Synthetic Aperture Radar ◽  
Image Fusion ◽  
Low Cost ◽  
Synthetic Aperture ◽  
Discrete Wavelet ◽  
Multi Layer Perceptron ◽  
Robust Adaptive ◽  
Sar Imagery ◽  
Design Regularization ◽  
Aperture Radar

This paper presents a novel multi-layer perceptron (MLP) based image fusion technique, which fuses two synthetic aperture radar (SAR) images, obtained from the same spatial reflectivity map, acquired with a conventional low-cost fractional synthetic aperture radar (Fr-SAR) system, enhanced via two different methodologies. The first image is enhanced using the traditional descriptive experiment design regularization (DEDR) framework through the projection onto convex solution sets (POCS) method; the second image is enhanced with the DEDR framework by incorporating the robust adaptive spatial filtering (RASF) solution operator. This work describes a MLP based technique applied to the pixel level multi-focus fusion problem characterized by the use of image windows with the idea of reducing noise and determining which pixel is clearer between the two images. Experimental results show that the proposed novel method outperforms the discrete wavelet transform based most competing approach.

scholarly journals Refocusing of Multiple Moving Targets Based on the Joint Sparse Processing of One Channel Synthetic Aperture Radar Imagery Patches

Electronics ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 1215 ◽  
Author(s):  
Xin Wang ◽  
Ling Qiao
Keyword(s):  
Synthetic Aperture Radar ◽  
Moving Objects ◽  
Radar Data ◽  
Synthetic Aperture ◽  
Moving Targets ◽  
Lp Norm ◽  
Radar Imagery ◽  
Sar Imagery ◽  
Norm Constraint ◽  
Aperture Radar

A sparse-based refocusing methodology for multiple slow-moving targets (MTs) located inside strong clutter regions is proposed in this paper. The defocused regions of MTs in synthetic aperture radar (SAR) imagery were utilized here instead of the whole original radar data. A joint radar projection operator for the static and moving objects was formulated and employed to construct an optimization problem. The Lp norm constraint was utilized to promote the separation of MT data and the suppression of clutter. After the joint sparse imaging processing, the energy of strong static targets could be suppressed significantly in the reconstructed MT imagery. The static scene imagery could be derived simultaneously without the defocused MT. Finally, numerical simulations were used verify the validity and robustness of the proposed methodology.

Better Utilization of SAR Dynamic Range

1977 ◽  
Vol 21 (3) ◽  
pp. 235-240
Author(s):  
Edward J. Dragavon
Keyword(s):  
Computer Simulation ◽  
Synthetic Aperture Radar ◽  
Real Time ◽  
Image Enhancement ◽  
Dynamic Range ◽  
Synthetic Aperture ◽  
Analytic Methods ◽  
Sar Imagery ◽  
Gray Shade ◽  
Aperture Radar

Three general classes of image enhancement techniques for synthetic aperture radar (SAR) video were investigated through non-real-time computer simulation. The general categories were 1) monochromatic adaptive gray shade transformations, 2) pseudocolor encoding, and 3) feature analytic methods. The class of feature analytic techniques was found to have the greatest potential for improving the operational utility of SAR imagery.

Ship hull characteristics from surface wake synthetic aperture radar (SAR) imagery

1996 ◽  
Vol 23 (5) ◽  
pp. 363-383 ◽  
Author(s):  
Owen M. Griffin ◽  
Henry T. Wang ◽  
Guy A. Meadows
Keyword(s):  
Synthetic Aperture Radar ◽  
Ship Hull ◽  
Synthetic Aperture ◽  
Sar Imagery ◽  
Aperture Radar
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