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Multispectral Image Compression Based on DSC Combined with CCSDS-IDC

Jin Li, Fei Xing, Ting Sun, Zheng You
2014 The Scientific World Journal  
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

Sanchita Rani Das, Md. Al Mamun, Md. Ali Hossain
2021 International Journal of Computer Applications  
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

R.L. Davidson, C.P. Bridges
2016 2016 IEEE International Conference on Imaging Systems and Techniques (IST)  
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

S.R. Tate
1997 IEEE transactions on computers  
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]

Tretter Daniel, Memon Nasir, Charles A. Bouman
2005 Handbook of Image and Video Processing  
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

Anju Asokan, J. Anitha, Monica Ciobanu, Andrei Gabor, Antoanela Naaji, D. Jude Hemanth
2020 Applied Sciences  
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

Guoxia Yu, Tanya Vladimirova, Xiaofeng Wu, Martin N. Sweeting
2008 2008 NASA/ESA Conference on Adaptive Hardware and Systems  
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

Xiaolin Wu, N. Memon
2000 IEEE Transactions on Image Processing  
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

D. Rocchini, C. Ricotta, A. Chiarucci
2007 Applied Vegetation Science  
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

Anil B. Gavade, Vijay S. Rajapurohit
2018 Zenodo  
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

Lilian N. Faria, Leila M. G. Fonseca, Max H. M. Costa
2012 Journal of Electrical and Computer Engineering  
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

Maryam Ouhami, Adel Hafiane, Youssef Es-Saady, Mohamed El Hajji, Raphael Canals
2021 Remote Sensing  
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

Md. AlMamun, Md. Nazrul Islam Mondal, Boshir Ahmed
2014 International Journal of Computer Applications  
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

Fanqiang Kong, Kedi Hu, Yunsong Li, Dan Li, Xin Liu, Tariq S. Durrani
2022 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
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]

Mingmin Zhao, Peder A. Olsen, Ranveer Chandra
2021 arXiv   pre-print
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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