Aircraft recognition in low-resolution SAR imagery using peak feature matching

2015 ◽  
Author(s):  
Zhaodong Niu ◽  
Jiameng Pan ◽  
Chenglong Lin ◽  
Zengping Chen
Keyword(s):  
Feature Matching ◽  
Low Resolution ◽  
Sar Imagery

Timely Low Resolution SAR Imagery To Support Floodplain Modelling: a Case Study Review

2011 ◽  
Vol 32 (3) ◽  
pp. 255-269 ◽  
Author(s):  
Giuliano Di Baldassarre ◽  
Guy Schumann ◽  
Luigia Brandimarte ◽  
Paul Bates
Keyword(s):  
Low Resolution ◽  
Study Review ◽  
Sar Imagery

scholarly journals AUTOMATIC MAPPING OF GLACIER BASED ON SAR IMAGERY BY BENEFITS OF FREELY OPTICAL AND THERMAL DATA

2015 ◽  
Vol XL-3/W2 ◽  
pp. 47-51
Author(s):  
L. Fang ◽  
L. Hoegner ◽  
U. Stilla
Keyword(s):  
Land Surface ◽  
Low Resolution ◽  
Glacier Surface ◽  
Thermal Data ◽  
Automatic Mapping ◽  
Resources Evaluation ◽  
Sar Imagery ◽  
Normalized Difference Snow Index ◽  
Occurrence Matrix

For many research applications like water resources evaluation, determination of glacier specific changes, and for calculation of the past and future contribution of glaciers to sea-level change, parameters about the size and spatial distribution of glaciers is crucial. In this paper, an automatic method for determination of glacier surface area using single track high resolution TerraSAR-X imagery by benefits of low resolution optical and thermal data is presented. Based on the normalized difference snow index (NDSI) and land surface temperature (LST) map generated from optical and thermal data combined with a surface slope data, a low resolution binary mask was derived used for the supervised classification of glacier using SAR imagery. Then, a set of suitable features is derived from the SAR intensity image, such as the texture information generated based on the gray level co-occurrence matrix (GLCM), and the intensity values. With these features, the glacier surface is discriminated from the background by Random Forests (RF) method.

scholarly journals Precise and Robust Ship Detection for High-Resolution SAR Imagery Based on HR-SDNet

2020 ◽  
Vol 12 (1) ◽  
pp. 167 ◽  
Author(s):  
Shunjun Wei ◽  
Hao Su ◽  
Jing Ming ◽  
Chen Wang ◽  
Min Yan ◽  
...  
Keyword(s):  
High Resolution ◽  
Detection Performance ◽  
Evaluation Metrics ◽  
Sar Image ◽  
Low Resolution ◽  
Feature Maps ◽  
Ship Detection ◽  
Feature Pyramid ◽  
Sar Imagery ◽  
Performance Gains

Ship detection in high-resolution synthetic aperture radar (SAR) imagery is a challenging problem in the case of complex environments, especially inshore and offshore scenes. Nowadays, the existing methods of SAR ship detection mainly use low-resolution representations obtained by classification networks or recover high-resolution representations from low-resolution representations in SAR images. As the representation learning is characterized by low resolution and the huge loss of resolution makes it difficult to obtain accurate prediction results in spatial accuracy; therefore, these networks are not suitable to ship detection of region-level. In this paper, a novel ship detection method based on a high-resolution ship detection network (HR-SDNet) for high-resolution SAR imagery is proposed. The HR-SDNet adopts a novel high-resolution feature pyramid network (HRFPN) to take full advantage of the feature maps of high-resolution and low-resolution convolutions for SAR image ship detection. In this scheme, the HRFPN connects high-to-low resolution subnetworks in parallel and can maintain high resolution. Next, the Soft Non-Maximum Suppression (Soft-NMS) is used to improve the performance of the NMS, thereby improving the detection performance of the dense ships. Then, we introduce the Microsoft Common Objects in Context (COCO) evaluation metrics, which provides not only the higher quality evaluation metrics average precision (AP) for more accurate bounding box regression, but also the evaluation metrics for small, medium and large targets, so as to precisely evaluate the detection performance of our method. Finally, the experimental results on the SAR ship detection dataset (SSDD) and TerraSAR-X high-resolution images reveal that (1) our approach based on the HRFPN has superior detection performance for both inshore and offshore scenes of the high-resolution SAR imagery, which achieves nearly 4.3% performance gains compared to feature pyramid network (FPN) in inshore scenes, thus proving its effectiveness; (2) compared with the existing algorithms, our approach is more accurate and robust for ship detection of high-resolution SAR imagery, especially inshore and offshore scenes; (3) with the Soft-NMS algorithm, our network performs better, which achieves nearly 1% performance gains in terms of AP; (4) the COCO evaluation metrics are effective for SAR image ship detection; (5) the displayed thresholds within a certain range have a significant impact on the robustness of ship detectors.

scholarly journals Surge-front propagation and velocities during the early-1993–95 surge of Bering Glacier, Alaska, U.S.A., from sequential SAR imagery

2003 ◽  
Vol 36 ◽  
pp. 37-44 ◽  
Author(s):  
James J. Roush ◽  
Craig S. Lingle ◽  
Richard M. Guritz ◽  
Dennis R. Fatland ◽  
Vera A. Voronina
Keyword(s):  
Feature Matching ◽  
Compressive Strain ◽  
Central Area ◽  
Front Propagation ◽  
Front Surface ◽  
Uniform Grid ◽  
Late Winter ◽  
Strain Rates ◽  
Bering Glacier ◽  
Sar Imagery

AbstractThe initiation and propagation of the 1993–95 surge of Bering Glacier, Alaska, U.S.A., was observed using ERS-1 synthetic aperture radar(SAR) imagery. Images were acquired before and during the surge, between November 1992 and October 1993. Terrain-corrected and co-registered imagery was used to measure the propagation of the surge front. Surface undulations interpreted to be evidence of accelerated flow, indicating surge initiation in late winter, were observed in the 26 March 1993 image. From 19 May to 25 August 1993, the mean propagation velocity of the surge front was 90 m d−1. The surge reached the terminus shortly after 25 August 1993. The central area of the calving terminus then advanced into proglacial Vitus Lake at a mean rate of 19 md−1 between 9 August and 18 October 1993. Feature matching was used to measure discrete velocity vectors between 9 August and 13 September; the vectors were kriged onto a uniform grid and used to compute the principal strain rates. Shattering of the calving front and dramatically increased iceberg calving were accompanied by high compressive strain rates immediately up-glacier from the calving front.

Monthly flooded area classification using low resolution SAR imagery in the Sudd wetland from 2007 to 2011

2017 ◽  
Vol 194 ◽  
pp. 205-218 ◽  
Author(s):  
Daniel C. Wilusz ◽  
Benjamin F. Zaitchik ◽  
Martha C. Anderson ◽  
Christopher R. Hain ◽  
M. Tugrul Yilmaz ◽  
...  
Keyword(s):  
Low Resolution ◽  
Sar Imagery ◽  
Flooded Area ◽  
Area Classification

Word-Finding Support From Mobile Technology Benefits a Woman With Aphasia

2015 ◽  
Vol 24 (1) ◽  
pp. 26-39 ◽  
Author(s):  
Yvonne Gillette
Keyword(s):  
Mobile Technology ◽  
Clinical Education ◽  
Augmentative And Alternative Communication ◽  
Feature Matching ◽  
Mobile Technologies ◽  
Alternative Communication ◽  
Alternative Intervention ◽  
Communication Assessment ◽  
Word Finding ◽  
Intervention Costs

Mobile technology provides a solution for individuals who require augmentative and alternative intervention. Principles of augmentative and alternative communication assessment and intervention, such as feature matching and the participation model, developed with dedicated speech-generating devices can be applied to these generic mobile technologies with success. This article presents a clinical review of an adult with aphasia who reached her goals for greater communicative participation through mobile technology. Details presented include device selection, sequence of intervention, and funding issues related to device purchase and intervention costs. Issues related to graduate student clinical education are addressed. The purpose of the article is to encourage clinicians to consider mobile technology when intervening with an individual diagnosed with mild receptive and moderate expressive aphasia featuring word-finding difficulties.

Caricaturing as a general method to improve poor face recognition: Evidence from low-resolution images, other-race faces, and older adults.

2019 ◽  
Vol 25 (2) ◽  
pp. 256-279 ◽  
Author(s):  
Amy Dawel ◽  
Tsz Ying Wong ◽  
Jodie McMorrow ◽  
Callin Ivanovici ◽  
Xuming He ◽  
...  
Keyword(s):  
Older Adults ◽  
Face Recognition ◽  
Low Resolution ◽  
General Method ◽  
Low Resolution Images
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