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Multispectral Image Compression Based on DSC Combined with CCSDS-IDC
2014
The Scientific World Journal
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A series of multispectral images is used to test our algorithm. ...
Remote sensing multispectral image compression encoder requires low complexity, high robust, and high performance because it usually works on the satellite where the resources, such as power, memory, and ...
Introduction Remote sensing multispectral images are obtained by optical multispectral camera carried on the satellite imaging multiple contiguous narrow bands of the same objects [1, 2] . ...
doi:10.1155/2014/738735
pmid:25110741
pmcid:PMC4119683
fatcat:cfu6ffqbrrfbleueyjtedqhr3e
Temporal Gradient based Satellite Image Compression
2021
International Journal of Computer Applications
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Due to limited transmission rate, remote sensed satellite images needs to be compressed before being delivered to the user. ...
The recent advancement in spatial, spectral and temporal resolution of satellite images has make it possible to use the images in these vital and world-wide challenging applications. ...
The recent advancement in spatial, spectral and temporal resolution of satellite images has make it possible to use the images in these vital and world-wide thought-provoking applications. ...
doi:10.5120/ijca2021921102
fatcat:b7ot3dxnojfrvmhmltqn62wcvi
Adaptive multispectral GPU accelerated architecture for Earth Observation satellites
2016
2016 IEEE International Conference on Imaging Systems and Techniques (IST)
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This research explores the selection and implementation of state-of-the-art multidimensional image compression algorithms and proposes a new onboard data processing architecture, to help alleviate the ...
This bottleneck must be alleviated in order for EO satellites to continue to efficiently provide high quality and increasing quantities of payload data. ...
This must be alleviated in order for EO satellites to deliver the quality and quantity of payload data expected by reliant applications. ...
doi:10.1109/ist.2016.7738208
fatcat:pwydrjemmng53hsgyuhg7rsbqa
Band ordering in lossless compression of multispectral images
1997
IEEE transactions on computers
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Abstract: In this paper, we consider a model of lossless image compression in which each band of a multispectral image is coded using a prediction function involving values from a previously coded band ...
The results show that the techniques described here hold great promise for application to real-world compression needs. ...
The author would like to thank Doreen Revis for her help with various aspects of the CM-5, Jim Tilton, Manohar Mareboyana, Gene Feldman, and Mary James for supplying test data, and Sarah Blanton for providing ...
doi:10.1109/12.588062
fatcat:m7u5lctirrdffgkxrwwhxblk3i
Multispectral Image Coding
[chapter]
2005
Handbook of Image and Video Processing
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Hu, Wang, and Cahill propose linear prediction algorithms for the lossy compression of multispectral MR images [11] . ...
Gupta and Gersho propose a feature predictive vector quantization approach to the compression of multispectral images [8] . ...
doi:10.1016/b978-012119792-6/50107-8
fatcat:ock34euztja5dkf7u6h3scmbby
Image Processing Techniques for Analysis of Satellite Images for Historical Maps Classification—An Overview
2020
Applied Sciences
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Wrong selection of methods will lead to inferior results for a specific application. This work highlights the methods and the suitable satellite imaging methods associated with these applications. ...
This work will help support the selection of innovative solutions for the different problems associated with satellite image processing applications. ...
The main problem in multispectral image is based on how to store the different multispectral bands and how these are compressed effectively. ...
doi:10.3390/app10124207
fatcat:zlttedt4qzht7aijl6alox43ky
A New High-Level Reconfigurable Lossless Image Compression System for Space Applications
2008
2008 NASA/ESA Conference on Adaptive Hardware and Systems
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On board image data compression is an important feature of satellite remote sensing payloads. Reconfigurable Intellectual Property (IP) cores can enable change of functionality or modifications. ...
A new and efficient lossless image compression scheme for space applications is proposed. ...
Acknowledgments The authors gratefully acknowledge the provision of satellite images from SSTL and DMC International Imaging for the experimental results in this paper. ...
doi:10.1109/ahs.2008.56
dblp:conf/ahs/YuVWS08
fatcat:2igmbkxxevh5lb2ygz7q2ns2qu
Context-based lossless interband compression-extending CALIC
2000
IEEE Transactions on Image Processing
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Interband coding techniques are needed for effective compression of multispectral images like color images and remotely sensed images. ...
On some types of multispectral images, interband CALIC can lead to a reduction in bit rate of more than 20% as compared to intraband CALIC. ...
ACKNOWLEDGMENT The authors would like to thank W. Choi for providing assistance in implementing the proposed technique. ...
doi:10.1109/83.846242
pmid:18255470
fatcat:3q3axsncvbgd3cqigxmrhzxtg4
Using satellite imagery to assess plant species richness: The role of multispectral systems
2007
Applied Vegetation Science
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interval is the most adequate for predicting species richness by means of linear regression analysis. ...
is an effective tool for compressing multispectral data without loss of information. ...
Loiselle for his suggestions on satellite image radiometric correction. ...
doi:10.1111/j.1654-109x.2007.tb00431.x
fatcat:kccp5fj6bje6ngqa6ysbbewgwq
Multispectral Super Resolution And Image Quality Assessment Comparative Analysis
2018
Zenodo
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The satellite image resolution alludes to highest accuracy to capture finer details from scene. This paper addresses five different techniques to improve resolution of multi spectral satellite image. ...
Super resolution (SR) is commercial algorithm to improve resolution of satellite image when we compare with image fusion. https://www.ijiert.org/paper-details?paper_id=140590 ...
ACKNOWLEDGEMENT We would like to express our heartily gratitude to Principal, KLS GIT, Belgaum and KLS Society for providing opportunity to do research work. ...
doi:10.5281/zenodo.1468517
fatcat:nhdtf4om65ayjeh5z55mx3n74m
Performance Evaluation of Data Compression Systems Applied to Satellite Imagery
2012
Journal of Electrical and Computer Engineering
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sensor of the CBERS-2B satellite. ...
Prediction-based compression systems, such as DPCM and JPEG-LS, and transform-based compression systems, such as CCSDS-IDC and JPEG-XR, were tested over twenty multispectral (5-band) images from CCD optical ...
Acknowledgments This project was supported by a fellowship from CNPq (National Counsel of Technological and Scientific Development), Brazil. ...
doi:10.1155/2012/471857
fatcat:5thx3r6t7vew7n366tdyf546xi
Computer Vision, IoT and Data Fusion for Crop Disease Detection Using Machine Learning: A Survey and Ongoing Research
2021
Remote Sensing
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It lists traditional and deep learning methods associated with the main data acquisition modalities, namely IoT, ground imaging, unmanned aerial vehicle imaging and satellite imaging. ...
A growing body of literature recognizes the importance of using data from different types of sensors and machine learning approaches to build models for detection, prediction, analysis, assessment, etc ...
Table 3 details commercial satellite sensors collecting multispectral images with a spatial resolution from 0.5 m to 30 m (Satellite Imaging Corporation (SIC)). ...
doi:10.3390/rs13132486
fatcat:f6u2vvmgvjggrhoqsph6odas3i
Evaluating Temporal Uncertainty of Multi-temporal Images for Geographical Deviance
2014
International Journal of Computer Applications
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Multi-temporal satellite images exhibit high amount of correlation in spatial, spectral and temporal domain. ...
The key measure of data compaction entropy will be exploited in this case to better understand the features dependency. General Terms Image Processing. ...
This has been extensively studied by applying a linear prediction algorithm to predict the recent image from reference image and then residual entropy has been calculated [13] . ...
doi:10.5120/18141-9339
fatcat:c52vclz5nvai5cycjw3kftgkae
A Spectral-Spatial Feature Extraction Method with Polydirectional CNN for Multispectral Image Compression
2022
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Convolutional neural networks (CNN) has been widely used in the research of multispectral image compression, but they still face the challenge of extracting spectral feature effectively while preserving ...
In this article, a novel spectral-spatial feature extraction method is proposed with polydirectional CNN (SSPC) for multispectral image compression. ...
Differential pulse code modulation (DPCM) [12] is one of the most basic predictive coding algorithms. In view of the characteristic of multispectral image compression, Mielikainen et al. ...
doi:10.1109/jstars.2022.3158281
fatcat:epbunspphjacrenkzdcovx2iiu
Seeing Through Clouds in Satellite Images
[article]
2021
arXiv
pre-print
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This paper presents a neural-network-based solution to recover pixels occluded by clouds in satellite images. ...
We leverage radio frequency (RF) signals in the ultra/super-high frequency band that penetrate clouds to help reconstruct the occluded regions in multispectral images. ...
In Figure 8 we show an application of satellite imaging to agriculture. ...
arXiv:2106.08408v1
fatcat:jzxkeywgiba7rbtukzona4iagy
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