On-orbit thermal distortion and optical performance evaluation of FORMOSAT-5 remote sensing instrument

2012 ◽  
Author(s):  
Chen Ching-Wei ◽  
Chen Chia-Ray ◽  
Cheng-En Ho ◽  
Mei-Yi Yang ◽  
Shenq-Tsong Chang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Performance Evaluation ◽  
Thermal Distortion ◽  
Optical Performance

scholarly journals Performance Evaluation of Single-Label and Multi-Label Remote Sensing Image Retrieval Using a Dense Labeling Dataset

2018 ◽  
Vol 10 (6) ◽  
pp. 964 ◽  
Author(s):  
Zhenfeng Shao ◽  
Ke Yang ◽  
Weixun Zhou
Keyword(s):  
Remote Sensing ◽  
Performance Evaluation ◽  
Deep Learning ◽  
Image Retrieval ◽  
Semantic Segmentation ◽  
Semantic Content ◽  
Remote Sensing Image ◽  
Remote Sensing Images ◽  
Benchmark Datasets ◽  
Feature Based

Benchmark datasets are essential for developing and evaluating remote sensing image retrieval (RSIR) approaches. However, most of the existing datasets are single-labeled, with each image in these datasets being annotated by a single label representing the most significant semantic content of the image. This is sufficient for simple problems, such as distinguishing between a building and a beach, but multiple labels and sometimes even dense (pixel) labels are required for more complex problems, such as RSIR and semantic segmentation.We therefore extended the existing multi-labeled dataset collected for multi-label RSIR and presented a dense labeling remote sensing dataset termed "DLRSD". DLRSD contained a total of 17 classes, and the pixels of each image were assigned with 17 pre-defined labels. We used DLRSD to evaluate the performance of RSIR methods ranging from traditional handcrafted feature-based methods to deep learning-based ones. More specifically, we evaluated the performances of RSIR methods from both single-label and multi-label perspectives. These results demonstrated the advantages of multiple labels over single labels for interpreting complex remote sensing images. DLRSD provided the literature a benchmark for RSIR and other pixel-based problems such as semantic segmentation.

Ground testing system for detecting optical performance of space remote sensing spectrometer

2017 ◽  
Vol 32 (3) ◽  
pp. 206-212
Author(s):  
王 岩 WANG Yan ◽  
杨小虎 YANG Xiao-hu ◽  
王金玲 WANG Jin-ling ◽  
王淑荣 WANG Shu-rong
Keyword(s):  
Remote Sensing ◽  
Testing System ◽  
Optical Performance ◽  
Ground Testing

Edge-lit sine-shape wedged light guides: Design, optical simulation, laser-remelting-based precision fabrication, and optical performance evaluation

2020 ◽  
Vol 66 ◽  
pp. 333-346 ◽  
Author(s):  
Evgueni V. Bordatchev ◽  
Moritz Küpper ◽  
Srdjan J. Cvijanovic ◽  
Edgar Willenborg ◽  
Nicolas Milliken ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Optical Simulation ◽  
Optical Performance ◽  
Laser Remelting ◽  
Light Guides

Performance evaluation of radar and satellite rainfalls for Typhoon Morakot over Taiwan: Are remote-sensing products ready for gauge denial scenario of extreme events?

2013 ◽  
Vol 506 ◽  
pp. 4-13 ◽  
Author(s):  
Sheng Chen ◽  
Yang Hong ◽  
Qing Cao ◽  
Pierre-Emmanuel Kirstetter ◽  
Jonathan J. Gourley ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Performance Evaluation ◽  
Extreme Events ◽  
Typhoon Morakot
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