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Relevant bibliographies by topics / SAR raw data compression

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Dissertations / Theses
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Academic literature on the topic 'SAR raw data compression'

Author: Grafiati

Published: 14 March 2023

Last updated: 31 July 2025

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Journal articles on the topic "SAR raw data compression"

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Parkes, S. M., and H. L. Clifton. "The compression of raw SAR and SAR image data." International Journal of Remote Sensing 20, no. 18 (1999): 3563–81. http://dx.doi.org/10.1080/014311699211200.

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Pascazio, V., and G. Schirinzi. "SAR raw data compression by subband coding." IEEE Transactions on Geoscience and Remote Sensing 41, no. 5 (2003): 964–76. http://dx.doi.org/10.1109/tgrs.2003.811811.

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Moureaux, J. M., P. Gauthier, M. Barlaud, and P. Bellemain. "Raw SAR data compression using vector quantization." International Journal of Remote Sensing 16, no. 16 (1995): 3179–87. http://dx.doi.org/10.1080/01431169508954621.

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Hua, Bin, Haiming Qi, Ping Zhang, and Xin Li. "Vector quantization for saturated SAR raw data compression." Advances in Space Research 45, no. 11 (2010): 1330–37. http://dx.doi.org/10.1016/j.asr.2010.01.007.

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Zeng, Shang Chun, Yun Xia Xie, Yi Xian Chen, and Zhao Da Zhu. "Study on an Algorithm for SAR Raw Data Compression." Applied Mechanics and Materials 380-384 (August 2013): 1495–98. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.1495.

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t is difficult to directly compress the raw data of synthetic aperture radar for its low relativity. In this paper, a new algorithm is put forward. Firstly range focusing is imposed to SAR raw data, which makes it have comparative high relativity, secondly a linear prediction is performed along the azimuth, lastly block adaptive quantization is used to the prediction difference series. The experiments manifest that with same bit rate, SQNR and SDNR of the algorithm proposed in this paper surpass that of BAQ algorithm. The calculation in this paper is far less than that of compression method af

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Zeng, Shang Chun, Xian Lin Deng, Yi Xian Chen, Yun Xia Xie, and Zhao Da Zhu. "A Compression Algorithm for SAR Data after Range Focusing." Advanced Materials Research 694-697 (May 2013): 2877–80. http://dx.doi.org/10.4028/www.scientific.net/amr.694-697.2877.

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It is difficult to directly compress the raw data of synthetic aperture radar for its low relativity. In this paper, a new algorithm is put forward. Firstly range focusing is imposed to SAR raw data, which makes it have comparative high relativity, secondly a linear prediction is performed along the azimuth, lastly block adaptive quantization is used to the prediction difference series. The experiments manifest that with same bit rate, SQNR and SDNR of the algorithm proposed in this paper surpass that of BAQ algorithm. The calculation in this paper is far less than that of compression method a

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Pieterse, Chané, Warren P. Plessis, and Richard W. Focke. "Metrics to evaluate compression algorithms for raw SAR data." IET Radar, Sonar & Navigation 13, no. 3 (2019): 333–46. http://dx.doi.org/10.1049/iet-rsn.2018.5213.

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Qi, HaiMing, WeiDong Yu, and Xi Chen. "Piecewise linear mapping algorithm for SAR raw data compression." Science in China Series F: Information Sciences 51, no. 12 (2008): 2126–34. http://dx.doi.org/10.1007/s11432-008-0133-y.

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Minhui, Zhu, Peng Hailiang, Wu Yirong, and Qi Xuan. "Enhanced multistage vector quantization for SAR raw data compression." Journal of Electronics (China) 13, no. 2 (1996): 97–101. http://dx.doi.org/10.1007/bf02684748.

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Xuan, Qi, Zhu Minhui, and Peng Hailiang. "Rapid codebook search algorithm for SAR raw data compression." Journal of Electronics (China) 13, no. 2 (1996): 110–15. http://dx.doi.org/10.1007/bf02684750.

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Dissertations / Theses on the topic "SAR raw data compression"

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PRETTE, NICOLA. "Advanced methods and deep learning for video and satellite data compression." Doctoral thesis, Politecnico di Torino, 2022. http://hdl.handle.net/11583/2971610.

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Yang, Yun-zhi, Shun-ji Huang, and Jian-guo Wang. "The Realization Analysis of SAR Raw Data With Block Adaptive Vector Quantization Algorithm." International Foundation for Telemetering, 2003. http://hdl.handle.net/10150/605596.

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International Telemetering Conference Proceedings / October 20-23, 2003 / Riviera Hotel and Convention Center, Las Vegas, Nevada<br>In this paper, we discuss a Block Adaptive Vector Quantization(BAVQ) Algorithm for Synthetic Aperture Radar(SAR). And we discuss a realization method of BAVQ algorithm for SAR raw data compressing in digital signal processor. Using the algorithm and the digital signal processor, we have compressed the SIR_C/X_SAR data.

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Schmidt, Alfred Rudolf. "Secondary range compression for improved range/Doppler processing of SAR data with high squint." Thesis, University of British Columbia, 1986. http://hdl.handle.net/2429/26325.

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This thesis examines a new algorithm, to be called secondary range compression (SRC), for significantly improving the range resolution of the range/Doppler synthetic aperture radar (SAR) processing algorithm when the radar antenna is significantly squinted away from the zero Doppler direction. The algorithm was recently introduced by Jin and Wu [13] for application to the SEASAT SAR sensor. Significant extensions of their algorithm and models are presented. First the model of range broadening in the basic range/Doppler algorithm is extended by using a more general form for the range compresse

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McGuinness, Christopher. "Characterizing Remote Sensing Data Compression Distortion for Improved Automated Exploitation Performance." University of Dayton / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1524844209730534.

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Wilhelmy, Jochen [Verfasser], and Willi A. [Akademischer Betreuer] Kalender. "Lossless and Lossy Raw Data Compression in CT Imaging / Jochen Wilhelmy. Betreuer: Willi A. Kalender." Erlangen : Universitätsbibliothek der Universität Erlangen-Nürnberg, 2012. http://d-nb.info/1029374414/34.

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Bhattaram, Sneha. "Signal Compression Methods for a Wear Debris Sensor." University of Akron / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=akron1399201029.

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Brunham, Kalen B. "Development of an FPGA based wavelet transformer for the compression of raw SAR data." 2003. http://hdl.handle.net/1993/19838.

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Book chapters on the topic "SAR raw data compression"

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Shangchun, Zeng, Chen Yixian, Xia Ming, Xie Yunxia, and Zhu Zhaoda. "Study on a Compression Algorithm for SAR Raw Data." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37149-3_21.

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Sun, Li, Yuedong Zhang, Qun Zhang, and Miao Ma. "DT-CWT-Based Improved BAQ for Anti-Saturation SAR Raw Data Compression." In Lecture Notes in Computer Science. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23989-7_53.

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Capizzi, Giacomo, Salvatore Coco, Antonio Laudani, and Giuseppe Pappalardo. "A New Methodology for Synthetic Aperture Radar (SAR) Raw Data Compression Based on Wavelet Transform and Neural Networks." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24844-6_103.

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Yankelevsky, Yael, Arie Feuer, and Zvi Friedman. "Decomposition-Based Compression of Ultrasound Raw-Data." In Latent Variable Analysis and Signal Separation. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22482-4_61.

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Jensen, Søren Kejser, Christian Thomsen, and Torben Bach Pedersen. "ModelarDB: Integrated Model-Based Management of Time Series from Edge to Cloud." In Transactions on Large-Scale Data- and Knowledge-Centered Systems LIII. Springer Berlin Heidelberg, 2023. http://dx.doi.org/10.1007/978-3-662-66863-4_1.

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AbstractTo ensure critical infrastructure is operating as expected, high-quality sensors are increasingly installed. However, due to the enormous amounts of high-frequency time series they produce, it is impossible or infeasible to transfer or even store these time series in the cloud when using state-of-the-practice compression methods. Thus, simple aggregates, e.g., 1–10-minutes averages, are stored instead of the raw time series. However, by only storing these simple aggregates, informative outliers and fluctuations are lost. Many Time Series Management System (TSMS) have been proposed to e

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Guo, Yuhua, Shichao Jin, and Yuhong Guo. "Efficient Simulation of Airborne SAR Raw Data in Case of Motion Errors." In Electromagnetic Compatibility [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.99378.

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In the simulation of SAR raw data, it is well-known that the frequency-domain algorithm is more efficient than a time-domain algorithm, making it is more suitable for extended scene simulation. However, the frequency-domain algorithm is perhaps better suited for ideal linear motion and requires some degrees of approximations to take the nonlinear motion effects. This chapter presents an efficient simulation approach based on hybrid time and frequency-domain algorithms under certain assumptions. The algorithm has high efficiency and is suitable for the simulation of extended scenes, which deman

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Zhang, Yanjun, and Xiaoyu Sun. "Enhanced Object Recognition in Autonomous Driving through LiDAR Point Cloud Data Compression." In Vehicle Technology and Automotive Engineering [Working Title]. IntechOpen, 2025. https://doi.org/10.5772/intechopen.1009545.

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In autonomous driving, lidar-derived point cloud data is crucial for detecting objects and understanding the vehicle's environment. However, the large volume of raw data poses challenges in storage, transmission, and real-time processing. Compression of lidar point cloud data is vital, as it reduces data size without significantly losing geometric and semantic information, thus enhancing autonomous driving system performance. Compressed data enables swift and accurate object recognition, improving safety and reliability. This chapter examines current compression methodologies, their strengths,

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Arora, Shaifali Madan, and Kavita Khanna. "Block-Based Motion Estimation." In Research Anthology on Recent Trends, Tools, and Implications of Computer Programming. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-3016-0.ch029.

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Recent years have witnessed a great technological evolution in video display and capturing technologies leading to the development of new standards of video coding including MPEG-X, H.26X and HEVC. The cost of computations, storage and high bandwidth requirements makes a video data expensive in terms of transmission and storage. This makes video compression absolutely necessary prior to its transmission in order to accommodate for different transmission media's capabilities. Digital video compression technologies therefore have become an important part of the way we create, present, communicat

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Sangeeta, Bentham Science Publisher, Preeti Gulia, and Nasib Singh Gill. "Compressed Video-Based Classification for Efficient Video Analytics." In Video Data Analytics for Smart City Applications: Methods and Trends. BENTHAM SCIENCE PUBLISHERS, 2023. http://dx.doi.org/10.2174/9789815123715123010005.

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Videos have become a crucial part of human life nowadays and share a large proportion of internet traffic. Various video-based platforms govern the mass consumption of videos through analytics-based filtering and recommendations. Various video-based platforms govern their mass consumption by analytics-based filtering and recommendations. Video analytics is used to provide the most relevant responses to our searches, block inappropriate content, and disseminate videos to the relevant community. Traditionally, for video content-based analytics, a video is first decoded to a large raw format on t

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Sangeeta, Preeti Gulia, and Nasib Singh Gill. "Compressed Video-Based Classification for Efficient Video Analytics." In Video Data Analytics for Smart City Applications: Methods and Trends. BENTHAM SCIENCE PUBLISHERS, 2023. http://dx.doi.org/10.2174/9789815123708123010005.

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Videos have become a crucial part of human life nowadays and share a large proportion of internet traffic. Various video-based platforms govern the mass consumption of videos through analytics-based filtering and recommendations. Various video-based platforms govern their mass consumption by analytics-based filtering and recommendations. Video analytics is used to provide the most relevant responses to our searches, block inappropriate content, and disseminate videos to the relevant community. Traditionally, for video content-based analytics, a video is first decoded to a large raw format on t

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Conference papers on the topic "SAR raw data compression"

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Pilikos, Georgios, Mario Azcueta, Roberto Camarero, and Nicolas Floury. "Raw SAR Data Compression with Deep Learning." In IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2024. http://dx.doi.org/10.1109/igarss53475.2024.10641432.

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Asiyabi, Reza Mohammadi, Andrei Anghel, Adrian Focsa, et al. "Adaptation of Decoded Sentinel-1 SAR Raw Data for the Assessment of Novel Data Compression Methods." In IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2024. http://dx.doi.org/10.1109/igarss53475.2024.10642269.

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Martone, Michele, Nicola Gollin, Paola Rizzoli, Gerhard Krieger, Max Ghiglione, and Ernesto Imbembo. "Raw Data Compression Exploiting Model-Based Approaches and Artificial Intelligence For Present And Next-Generation SAR Systems." In IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2024. http://dx.doi.org/10.1109/igarss53475.2024.10640933.

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Hwang, Ji-Hwan, Jung-Hwan Song, Kwang Ho Choi, et al. "Bistatic SAR Raw Data Acquisition and Imaging with GPS Time-Synchronized Dual ECHO-SAR Systems." In IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2024. http://dx.doi.org/10.1109/igarss53475.2024.10640423.

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Zou, Bin, Dewu Wang, Ye Zhang, and Zhilu Wu. "Phase Information Reserved Polarimetric SAR Raw Data Compression." In 2012 Data Compression Conference (DCC). IEEE, 2012. http://dx.doi.org/10.1109/dcc.2012.49.

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Rane, Shantanu, Petros Boufounos, Anthony Vetro, and Yu Okada. "Low complexity efficient raw SAR data compression." In SPIE Defense, Security, and Sensing. SPIE, 2011. http://dx.doi.org/10.1117/12.884034.

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Magli, Enrico, and Gabriella Olmo. "Entropy-constrained predictive compression of SAR raw data." In International Symposium on Optical Science and Technology, edited by Mark S. Schmalz. SPIE, 2003. http://dx.doi.org/10.1117/12.454829.

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Kenge, Akanksha, M. S. Panse, Suyog Choudhari, Hitendra Pethkar, and Raymond Pinto. "Wavelet Transform Based Compression of Raw SAR Data." In 2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2021. http://dx.doi.org/10.1109/icccnt51525.2021.9579774.

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Wang, Min. "Raw SAR data compression by structurally random matrix based compressive sampling." In 2009 2nd Asian-Pacific Conference on Synthetic Aperture Radar (APSAR). IEEE, 2009. http://dx.doi.org/10.1109/apsar.2009.5374143.

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Li Ting, Wang Dongjin, and Liu Falin. "A Fast BAVQ Algorithm For SAR Raw Data Compression." In 2006 CIE International Conference on Radar. IEEE, 2006. http://dx.doi.org/10.1109/icr.2006.343339.

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Reports on the topic "SAR raw data compression"

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Down, Murray. PR686-203903-R02 Ongoing InSAR Geohazard Monitoring of Pipeline Right-of Ways in the Appalachian Mountains. Pipeline Research Council International, Inc. (PRCI), 2021. http://dx.doi.org/10.55274/r0012178.

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Ground displacement along pipeline corridors has the potential to compromise pipeline integrity. The Appalachian Mountain region is almost entirely classed as high landslide susceptibility by the United States Geological Survey (USGS) and crossed by numerous transmission pipelines and gathering lines. In phase I of this research project, 3vGeomatics successfully demonstrated a proof of concept on the effectiveness, reliability, and precision of using L-band ( ) SAR satellites for InSAR displacement monitoring of vegetated areas. The second phase of this project improved operational monitoring

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Nieland and Ying. L52105 Improvement in Performance in the Mark III Elastic Wave. Pipeline Research Council International, Inc. (PRCI), 2003. http://dx.doi.org/10.55274/r0011087.

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The Elastic Wave (EW) technology has a proven record of detecting longitudinal cracking in gas and liquid pipelines. However, the historical dig success rate for this inspection tool is only 1 in 4; i.e. for every four excavations carried out by pipeline operators, following an EW inspection, typically a crack or crack field will only be found at one of those excavations. This project set out to: Understand the ultrasonic data available to the inspection tool, establish whether there is information in the raw signal to differentiate between cracks and non-cracks, develop potential crack discri

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