Remote Sensing Data Compression

A huge amount of data is acquired nowadays by different remote sensing systems installed on satellites, aircrafts, and UAV. The acquired data then have to be transferred to image processing centres, stored and/or delivered to customers. In restricted scenarios, data compression is strongly desired o...

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Year of Publication:2021
Language:English
Physical Description:1 electronic resource (366 p.)
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100 1 |a Lukin, Vladimir  |4 edt 
245 1 0 |a Remote Sensing Data Compression 
260 |a Basel, Switzerland  |b MDPI - Multidisciplinary Digital Publishing Institute  |c 2021 
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520 |a A huge amount of data is acquired nowadays by different remote sensing systems installed on satellites, aircrafts, and UAV. The acquired data then have to be transferred to image processing centres, stored and/or delivered to customers. In restricted scenarios, data compression is strongly desired or necessary. A wide diversity of coding methods can be used, depending on the requirements and their priority. In addition, the types and properties of images differ a lot, thus, practical implementation aspects have to be taken into account. The Special Issue paper collection taken as basis of this book touches on all of the aforementioned items to some degree, giving the reader an opportunity to learn about recent developments and research directions in the field of image compression. In particular, lossless and near-lossless compression of multi- and hyperspectral images still remains current, since such images constitute data arrays that are of extremely large size with rich information that can be retrieved from them for various applications. Another important aspect is the impact of lossless compression on image classification and segmentation, where a reasonable compromise between the characteristics of compression and the final tasks of data processing has to be achieved. The problems of data transition from UAV-based acquisition platforms, as well as the use of FPGA and neural networks, have become very important. Finally, attempts to apply compressive sensing approaches in remote sensing image processing with positive outcomes are observed. We hope that readers will find our book useful and interesting 
546 |a English 
650 7 |a Technology: general issues  |2 bicssc 
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653 |a near-lossless hyperspectral image compression 
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653 |a integer-to-integer transforms 
653 |a graph signal processing 
653 |a compact data structure 
653 |a quadtree 
653 |a k2-tree 
653 |a k2-raster 
653 |a DACs 
653 |a 3D-CALIC 
653 |a M-CALIC 
653 |a hyperspectral images 
653 |a fully convolutional network 
653 |a semantic segmentation 
653 |a spectral image 
653 |a tensor decomposition 
653 |a HEVC 
653 |a intra coding 
653 |a JPEG 2000 
653 |a high bit-depth compression 
653 |a multispectral satellite images 
653 |a crop classification 
653 |a Landsat-8 
653 |a Sentinel-2 
653 |a Elias codes 
653 |a Simple9 
653 |a Simple16 
653 |a PForDelta 
653 |a Rice codes 
653 |a hyperspectral scenes 
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653 |a real time 
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653 |a JPEG2000 
653 |a EBCOT 
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653 |a transform 
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653 |a on-board processing 
653 |a GPU 
653 |a real-time performance 
653 |a UAV 
653 |a parallel computing 
653 |a remote sensing 
653 |a image quality 
653 |a image classification 
653 |a visual quality metrics 
653 |a spectral–spatial feature 
653 |a multispectral image compression 
653 |a partitioned extraction 
653 |a group convolution 
653 |a rate-distortion 
653 |a compressed sensing 
653 |a invertible projection 
653 |a coupled dictionary 
653 |a singular value 
653 |a task-driven learning 
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653 |a transform coding 
653 |a learned compression 
653 |a neural networks 
653 |a variational autoencoder 
653 |a complexity 
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653 |a real-time transmission 
653 |a UAVs 
653 |a compressive sensing 
653 |a synthetic aperture sonar 
653 |a underwater sonar imaging 
653 |a remote sensing data compression 
653 |a lossless compression 
653 |a compression impact 
653 |a computational complexity 
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700 1 |a Vozel, Benoit  |4 edt 
700 1 |a Serra-Sagristà, Joan  |4 edt 
700 1 |a Lukin, Vladimir  |4 oth 
700 1 |a Vozel, Benoit  |4 oth 
700 1 |a Serra-Sagristà, Joan  |4 oth 
906 |a BOOK 
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