Chen et al., 2020 - Google Patents
Rain-contaminated region segmentation of X-band marine radar images with an ensemble of SegNetsChen et al., 2020
View PDF- Document ID
- 3327318322161138765
- Author
- Chen X
- Huang W
- Haller M
- Pittman R
- Publication year
- Publication venue
- IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
External Links
Snippet
The presence of rain may blur surface wave signatures and cause additional radar backscatter, which negatively affects the performance of ocean remote sensing applications (eg, ocean surface wind and wave parameter measurement) using X-band marine radars. In …
- 230000011218 segmentation 0 title description 50
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
- G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. correcting range migration errors
- G01S13/9035—Particular SAR processing techniques not provided for elsewhere, e.g. squint mode, doppler beam-sharpening mode, spotlight mode, bistatic SAR, inverse SAR
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/95—Radar or analogous systems specially adapted for specific applications for meteorological use
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/28—Details of pulse systems
- G01S7/285—Receivers
- G01S7/292—Extracting wanted echo-signals
- G01S7/2923—Extracting wanted echo-signals based on data belonging to a number of consecutive radar periods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
- G06K9/0063—Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas
- G06K9/00657—Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas of vegetation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01W—METEOROLOGY
- G01W1/00—Meteorology
- G01W1/10—Devices for predicting weather conditions
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S3/00—Direction-finders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Chen et al. | Rain-contaminated region segmentation of X-band marine radar images with an ensemble of SegNets | |
| Chen et al. | Estimating tropical cyclone intensity by satellite imagery utilizing convolutional neural networks | |
| Chen et al. | Spatial–temporal convolutional gated recurrent unit network for significant wave height estimation from shipborne marine radar data | |
| Wang et al. | Sea ice concentration estimation during melt from dual-pol SAR scenes using deep convolutional neural networks: A case study | |
| Cooke et al. | Estimating sea ice concentration from SAR: Training convolutional neural networks with passive microwave data | |
| Chen et al. | Identification of rain and low-backscatter regions in X-band marine radar images: An unsupervised approach | |
| Huang et al. | Wave height estimation from X-band nautical radar images using temporal convolutional network | |
| Guo et al. | A deep learning model for green algae detection on SAR images | |
| Yang et al. | Evaluation and mitigation of rain effect on wave direction and period estimation from X-band marine radar images | |
| Liu et al. | Comparison of algorithms for wind parameters extraction from shipborne X-band marine radar images | |
| Celona et al. | Automated detection, classification, and tracking of internal wave signatures using X-band radar in the inner shelf | |
| Chen et al. | A novel scheme for extracting sea surface wind information from rain-contaminated X-band marine radar images | |
| Qiao et al. | WaveTransNet: A transformer-based network for global significant wave height retrieval from spaceborne GNSS-R data | |
| Liu et al. | GNSS-R global sea surface wind speed retrieval based on deep learning | |
| CN117217103B (en) | Satellite-borne SAR sea clutter generation method and system based on multi-scale attention mechanism | |
| WO2010127140A2 (en) | High-resolution wind measurements for offshore wind energy development | |
| Bu et al. | Machine learning methods for Earth observation and remote sensing using spaceborne GNSS reflectometry: Current status, challenges, and future prospects | |
| Liu et al. | CALC-2020: a new baseline land cover map at 10 m resolution for the circumpolar Arctic | |
| Jiang et al. | Sea-ice mapping of RADARSAT-2 imagery by integrating spatial contexture with textural features | |
| Komarov et al. | Assimilation of RCM data in the Canadian ice concentration analysis system | |
| Sun et al. | Annual change in the distribution and landscape health of mangrove ecosystems in China from 2016 to 2023 with Sentinel imagery | |
| Shi et al. | A clustering-based method for identifying and tracking squall lines | |
| Wang et al. | A submesoscale eddy identification dataset in the northwest Pacific Ocean derived from GOCI I chlorophyll a data based on deep learning | |
| CN120451772B (en) | A method for monitoring glacial lake morphology in data-scarce areas based on satellite remote sensing | |
| Colin et al. | Rainfall regression from C-band synthetic aperture radar using multitask generative adversarial networks |